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# Variable-width Variable-packed SIMD / Simple-V / Parallelism Extension Proposal

Key insight: Simple-V is intended as an abstraction layer to provide
a consistent "API" to parallelisation of existing *and future* operations.
*Actual* internal hardware-level parallelism is *not* required, such
that Simple-V may be viewed as providing a "compact" or "consolidated"
means of issuing multiple near-identical arithmetic instructions to an
instruction queue (FIFO), pending execution.

*Actual* parallelism, if added independently of Simple-V in the form
of Out-of-order restructuring (including parallel ALU lanes) or VLIW
implementations, or SIMD, or anything else, would then benefit *if*
Simple-V was added on top.

[[!toc ]]

# Introduction

This proposal exists so as to be able to satisfy several disparate
requirements: power-conscious, area-conscious, and performance-conscious
designs all pull an ISA and its implementation in different conflicting
directions, as do the specific intended uses for any given implementation.

The existing P (SIMD) proposal and the V (Vector) proposals,
whilst each extremely powerful in their own right and clearly desirable,
are also:

* Clearly independent in their origins (Cray and AndesStar v3 respectively)
  so need work to adapt to the RISC-V ethos and paradigm
* Are sufficiently large so as to make adoption (and exploration for
  analysis and review purposes) prohibitively expensive
* Both contain partial duplication of pre-existing RISC-V instructions
  (an undesirable characteristic)
* Both have independent, incompatible and disparate methods for introducing
  parallelism at the instruction level
* Both require that their respective parallelism paradigm be implemented
  along-side and integral to their respective functionality *or not at all*.
* Both independently have methods for introducing parallelism that
  could, if separated, benefit
  *other areas of RISC-V not just DSP or Floating-point respectively*.

There are also key differences between Vectorisation and SIMD (full
details outlined in the Appendix), the key points being:

* SIMD has an extremely seductively compelling ease of implementation argument:
  each operation is passed to the ALU, which is where the parallelism
  lies.  There is *negligeable* (if any) impact on the rest of the core
  (with life instead being made hell for compiler writers and applications
  writers due to extreme ISA proliferation).
* By contrast, Vectorisation has quite some complexity (for considerable
  flexibility, reduction in opcode proliferation and much more).
* Vectorisation typically includes much more comprehensive memory load
  and store schemes (unit stride, constant-stride and indexed), which
  in turn have ramifications: virtual memory misses (TLB cache misses)
  and even multiple page-faults... all caused by a *single instruction*,
  yet with a clear benefit that the regularisation of LOAD/STOREs can
  be optimised for minimal impact on caches and maximised throughput.
* By contrast, SIMD can use "standard" memory load/stores (32-bit aligned
  to pages), and these load/stores have absolutely nothing to do with the
  SIMD / ALU engine, no matter how wide the operand.  Simplicity but with
  more impact on instruction and data caches.

Overall it makes a huge amount of sense to have a means and method
of introducing instruction parallelism in a flexible way that provides
implementors with the option to choose exactly where they wish to offer
performance improvements and where they wish to optimise for power
and/or area (and if that can be offered even on a per-operation basis that
would provide even more flexibility).

Additionally it makes sense to *split out* the parallelism inherent within
each of P and V, and to see if each of P and V then, in *combination* with
a "best-of-both" parallelism extension, could be added on *on top* of
this proposal, to topologically provide the exact same functionality of
each of P and V.  Each of P and V then can focus on providing the best
operations possible for their respective target areas, without being
hugely concerned about the actual parallelism.

Furthermore, an additional goal of this proposal is to reduce the number
of opcodes utilised by each of P and V as they currently stand, leveraging
existing RISC-V opcodes where possible, and also potentially allowing
P and V to make use of Compressed Instructions as a result.

# Analysis and discussion of Vector vs SIMD

There are six combined areas between the two proposals that help with
parallelism (increased performance, reduced power / area) without
over-burdening the ISA with a huge proliferation of
instructions:

* Fixed vs variable parallelism (fixed or variable "M" in SIMD)
* Implicit vs fixed instruction bit-width (integral to instruction or not)
* Implicit vs explicit type-conversion (compounded on bit-width)
* Implicit vs explicit inner loops.
* Single-instruction LOAD/STORE.
* Masks / tagging (selecting/preventing certain indexed elements from execution)

The pros and cons of each are discussed and analysed below.

## Fixed vs variable parallelism length

In David Patterson and Andrew Waterman's analysis of SIMD and Vector
ISAs, the analysis comes out clearly in favour of (effectively) variable
length SIMD.  As SIMD is a fixed width, typically 4, 8 or in extreme cases
16 or 32 simultaneous operations, the setup, teardown and corner-cases of SIMD
are extremely burdensome except for applications whose requirements
*specifically* match the *precise and exact* depth of the SIMD engine.

Thus, SIMD, no matter what width is chosen, is never going to be acceptable
for general-purpose computation, and in the context of developing a
general-purpose ISA, is never going to satisfy 100 percent of implementors.

To explain this further: for increased workloads over time, as the
performance requirements increase for new target markets, implementors
choose to extend the SIMD width (so as to again avoid mixing parallelism
into the instruction issue phases: the primary "simplicity" benefit of
SIMD in the first place), with the result that the entire opcode space
effectively doubles with each new SIMD width that's added to the ISA.

That basically leaves "variable-length vector" as the clear *general-purpose*
winner, at least in terms of greatly simplifying the instruction set,
reducing the number of instructions required for any given task, and thus
reducing power consumption for the same.

## Implicit vs fixed instruction bit-width

SIMD again has a severe disadvantage here, over Vector: huge proliferation
of specialist instructions that target 8-bit, 16-bit, 32-bit, 64-bit, and
have to then have operations *for each and between each*.  It gets very
messy, very quickly.

The V-Extension on the other hand proposes to set the bit-width of
future instructions on a per-register basis, such that subsequent instructions
involving that register are *implicitly* of that particular bit-width until
otherwise changed or reset.

This has some extremely useful properties, without being particularly
burdensome to implementations, given that instruction decode already has
to direct the operation to a correctly-sized width ALU engine, anyway.

Not least: in places where an ISA was previously constrained (due for
whatever reason, including limitations of the available operand space),
implicit bit-width allows the meaning of certain operations to be
type-overloaded *without* pollution or alteration of frozen and immutable
instructions, in a fully backwards-compatible fashion.

## Implicit and explicit type-conversion

The Draft 2.3 V-extension proposal has (deprecated) polymorphism to help
deal with over-population of instructions, such that type-casting from
integer (and floating point) of various sizes is automatically inferred
due to "type tagging" that is set with a special instruction.  A register
will be *specifically* marked as "16-bit Floating-Point" and, if added
to an operand that is specifically tagged as "32-bit Integer" an implicit
type-conversion will take place *without* requiring that type-conversion
to be explicitly done with its own separate instruction.

However, implicit type-conversion is not only quite burdensome to
implement (explosion of inferred type-to-type conversion) but also is
never really going to be complete.  It gets even worse when bit-widths
also have to be taken into consideration.  Each new type results in
an increased O(N^2) conversion space that, as anyone who has examined
python's source code (which has built-in polymorphic type-conversion),
knows that the task is more complex than it first seems.

Overall, type-conversion is generally best to leave to explicit
type-conversion instructions, or in definite specific use-cases left to
be part of an actual instruction (DSP or FP)

## Zero-overhead loops vs explicit loops

The initial Draft P-SIMD Proposal by Chuanhua Chang of Andes Technology
contains an extremely interesting feature: zero-overhead loops.  This
proposal would basically allow an inner loop of instructions to be
repeated indefinitely, a fixed number of times.

Its specific advantage over explicit loops is that the pipeline in a DSP
can potentially be kept completely full *even in an in-order single-issue
implementation*.  Normally, it requires a superscalar architecture and
out-of-order execution capabilities to "pre-process" instructions in
order to keep ALU pipelines 100% occupied.

By bringing that capability in, this proposal could offer a way to increase
pipeline activity even in simpler implementations in the one key area
which really matters: the inner loop.

However when looking at much more comprehensive schemes
"A portable specification of zero-overhead loop control hardware
applied to embedded processors" (ZOLC), optimising only the single
inner loop seems inadequate, tending to suggest that ZOLC may be
better off being proposed as an entirely separate Extension.

## Single-instruction LOAD/STORE

In traditional Vector Architectures there are instructions which
result in multiple register-memory transfer operations resulting
from a single instruction.  They're complicated to implement in hardware,
yet the benefits are a huge consistent regularisation of memory accesses
that can be highly optimised with respect to both actual memory and any
L1, L2 or other caches.  In Hwacha EECS-2015-263 it is explicitly made
clear the consequences of getting this architecturally wrong:
L2 cache-thrashing at the very least.

Complications arise when Virtual Memory is involved: TLB cache misses
need to be dealt with, as do page faults.  Some of the tradeoffs are
discussed in <http://people.eecs.berkeley.edu/~krste/thesis.pdf>, Section
4.6, and an article by Jeff Bush when faced with some of these issues
is particularly enlightening
<https://jbush001.github.io/2015/11/03/lost-in-translation.html>

Interestingly, none of this complexity is faced in SIMD architectures...
but then they do not get the opportunity to optimise for highly-streamlined
memory accesses either.

With the "bang-per-buck" ratio being so high and the indirect improvement
in L1 Instruction Cache usage (reduced instruction count), as well as
the opportunity to optimise L1 and L2 cache usage, the case for including
Vector LOAD/STORE is compelling.

## Mask and Tagging (Predication)

Tagging (aka Masks aka Predication) is a pseudo-method of implementing
simplistic branching in a parallel fashion, by allowing execution on
elements of a vector to be switched on or off depending on the results
of prior operations in the same array position.

The reason for considering this is simple: by *definition* it
is not possible to perform individual parallel branches in a SIMD
(Single-Instruction, **Multiple**-Data) context.  Branches (modifying
of the Program Counter) will result in *all* parallel data having
a different instruction executed on it: that's just the definition of
SIMD, and it is simply unavoidable.

So these are the ways in which conditional execution may be implemented:

* explicit compare and branch: BNE x, y -> offs would jump offs
  instructions if x was not equal to y
* explicit store of tag condition: CMP x, y -> tagbit
* implicit (condition-code) such as ADD results in a carry, carry bit
  implicitly (or sometimes explicitly) goes into a "tag" (mask) register

The first of these is a "normal" branch method, which is flat-out impossible
to parallelise without look-ahead and effectively rewriting instructions.
This would defeat the purpose of RISC.

The latter two are where parallelism becomes easy to do without complexity:
every operation is modified to be "conditionally executed" (in an explicit
way directly in the instruction format *or* implicitly).

RVV (Vector-Extension) proposes to have *explicit* storing of the compare
in a tag/mask register, and to *explicitly* have every vector operation
*require* that its operation be "predicated" on the bits within an
explicitly-named tag/mask register.

SIMD (P-Extension) has not yet published precise documentation on what its
schema is to be: there is however verbal indication at the time of writing
that:

> The "compare" instructions in the DSP/SIMD ISA proposed by Andes will
> be executed using the same compare ALU logic for the base ISA with some
> minor modifications to handle smaller data types. The function will not
> be duplicated.

This is an *implicit* form of predication as the base RV ISA does not have
condition-codes or predication.  By adding a CSR it becomes possible
to also tag certain registers as "predicated if referenced as a destination".
Example:

    // in future operations from now on, if r0 is the destination use r5 as
    // the PREDICATION register
    SET_IMPLICIT_CSRPREDICATE r0, r5
    // store the compares in r5 as the PREDICATION register
    CMPEQ8 r5, r1, r2
    // r0 is used here.  ah ha!  that means it's predicated using r5!
    ADD8 r0, r1, r3

With enough registers (and in RISC-V there are enough registers) some fairly
complex predication can be set up and yet still execute without significant
stalling, even in a simple non-superscalar architecture.

(For details on how Branch Instructions would be retro-fitted to indirectly
predicated equivalents, see Appendix)

## Conclusions

In the above sections the five different ways where parallel instruction
execution has closely and loosely inter-related implications for the ISA and
for implementors, were outlined.  The pluses and minuses came out as
follows:

* Fixed vs variable parallelism: <b>variable</b>
* Implicit (indirect) vs fixed (integral) instruction bit-width: <b>indirect</b>
* Implicit vs explicit type-conversion: <b>explicit</b>
* Implicit vs explicit inner loops: <b>implicit but best done separately</b>
* Single-instruction Vector LOAD/STORE: <b>Complex but highly beneficial</b>
* Tag or no-tag: <b>Complex but highly beneficial</b>

In particular:

* variable-length vectors came out on top because of the high setup, teardown
  and corner-cases associated with the fixed width of SIMD.
* Implicit bit-width helps to extend the ISA to escape from
  former limitations and restrictions (in a backwards-compatible fashion),
  whilst also leaving implementors free to simmplify implementations
  by using actual explicit internal parallelism.
* Implicit (zero-overhead) loops provide a means to keep pipelines
  potentially 100% occupied in a single-issue in-order implementation
  i.e. *without* requiring a super-scalar or out-of-order architecture,
  but doing a proper, full job (ZOLC) is an entirely different matter.

Constructing a SIMD/Simple-Vector proposal based around four of these six
requirements would therefore seem to be a logical thing to do.

# Note on implementation of parallelism

One extremely important aspect of this proposal is to respect and support
implementors desire to focus on power, area or performance.  In that regard,
it is proposed that implementors be free to choose whether to implement
the Vector (or variable-width SIMD) parallelism as sequential operations
with a single ALU, fully parallel (if practical) with multiple ALUs, or
a hybrid combination of both.

In Broadcom's Videocore-IV, they chose hybrid, and called it "Virtual
Parallelism".  They achieve a 16-way SIMD at an **instruction** level
by providing a combination of a 4-way parallel ALU *and* an externally
transparent loop that feeds 4 sequential sets of data into each of the
4 ALUs.

Also in the same core, it is worth noting that particularly uncommon
but essential operations (Reciprocal-Square-Root for example) are
*not* part of the 4-way parallel ALU but instead have a *single* ALU.
Under the proposed Vector (varible-width SIMD) implementors would
be free to do precisely that: i.e. free to choose *on a per operation
basis* whether and how much "Virtual Parallelism" to deploy.

It is absolutely critical to note that it is proposed that such choices MUST
be **entirely transparent** to the end-user and the compiler.  Whilst
a Vector (varible-width SIM) may not precisely match the width of the
parallelism within the implementation, the end-user **should not care**
and in this way the performance benefits are gained but the ISA remains
straightforward.  All that happens at the end of an instruction run is: some
parallel units (if there are any) would remain offline, completely
transparently to the ISA, the program, and the compiler.

The "SIMD considered harmful" trap of having huge complexity and extra
instructions to deal with corner-cases is thus avoided, and implementors
get to choose precisely where to focus and target the benefits of their
implementation efforts, without "extra baggage".

# Instructions

By being a topological remap of RVV concepts, the following RVV instructions
remain exactly the same: VMPOP, VMFIRST, VEXTRACT, VINSERT, VMERGE, VSELECT,
VSLIDE, VCLASS and VPOPC.  Two instructions, VCLIP and VCLIPI, do not
have RV Standard equivalents, so are left out of Simple-V.
All other instructions from RVV are topologically re-mapped and retain
their complete functionality, intact.

## Instruction Format

The instruction format for Simple-V does not actually have *any* explicit
compare operations, *any* arithmetic, floating point or *any*
memory instructions.
Instead it *overloads* pre-existing branch operations into predicated
variants, and implicitly overloads arithmetic operations and LOAD/STORE
depending on CSR configurations for vector length, bitwidth and
predication.  *This includes Compressed instructions* as well as any
future instructions and Custom Extensions.

* For analysis of RVV see [[v_comparative_analysis]] which begins to
  outline topologically-equivalent mappings of instructions
* Also see Appendix "Retro-fitting Predication into branch-explicit ISA"
  for format of Branch opcodes.

**TODO**: *analyse and decide whether the implicit nature of predication
as proposed is or is not a lot of hassle, and if explicit prefixes are
a better idea instead.  Parallelism therefore effectively may end up
as always being 64-bit opcodes (32 for the prefix, 32 for the instruction)
with some opportunities for to use Compressed bringing it down to 48.
Also to consider is whether one or both of the last two remaining Compressed
instruction codes in Quadrant 1 could be used as a parallelism prefix,
bringing parallelised opcodes down to 32-bit (when combined with C)
and having the benefit of being explicit.*

## Branch Instruction:

This is the overloaded table for Integer-base Branch operations.  Opcode
(bits 6..0) is set in all cases to 1100011.

[[!table  data="""
31    .. 25 |24 ... 20 | 19 15 | 14  12 | 11 ..  8 | 7       | 6 ... 0 |
imm[12,10:5]| rs2      | rs1   | funct3 | imm[4:1] | imm[11] | opcode  |
7           | 5        | 5     | 3      | 4             | 1  | 7       |
reserved    | src2     | src1  | BPR    | predicate rs3     || BRANCH  |
reserved    | src2     | src1  | 000    | predicate rs3     || BEQ     |
reserved    | src2     | src1  | 001    | predicate rs3     || BNE     |
reserved    | src2     | src1  | 010    | predicate rs3     || rsvd    |
reserved    | src2     | src1  | 011    | predicate rs3     || rsvd    |
reserved    | src2     | src1  | 100    | predicate rs3     || BLE     |
reserved    | src2     | src1  | 101    | predicate rs3     || BGE     |
reserved    | src2     | src1  | 110    | predicate rs3     || BLTU    |
reserved    | src2     | src1  | 111    | predicate rs3     || BGEU    |
"""]]

Below is the overloaded table for Floating-point Predication operations.
Interestingly no change is needed to the instruction format because
FP Compare already stores a 1 or a zero in its "rd" integer register
target, i.e. it's not actually a Branch at all: it's a compare.
The target needs to simply change to be a predication bitfield (done
implicitly).

As with
Standard RVF/D/Q, Opcode (bits 6..0) is set in all cases to 1010011.
Likewise Single-precision, fmt bits 26..25) is still set to 00.
Double-precision is still set to 01, whilst Quad-precision
appears not to have a definition in V2.3-Draft (but should be unaffected).

It is however noted that an entry "FNE" (the opposite of FEQ) is missing,
and whilst in ordinary branch code this is fine because the standard
RVF compare can always be followed up with an integer BEQ or a BNE (or
a compressed comparison to zero or non-zero), in predication terms that
becomes more of an impact as an explicit (scalar) instruction is needed
to invert the predicate bitmask.  An additional encoding funct3=011 is
therefore proposed to cater for this.

[[!table  data="""
31 .. 27| 26 .. 25 |24 ... 20 | 19 15 | 14  12 | 11 .. 7  | 6 ... 0 |
funct5  | fmt      | rs2      | rs1   | funct3 | rd       | opcode  |
5       | 2        | 5        | 5     | 3      | 4        | 7       |
10100   | 00/01/11 | src2     | src1  | 010    | pred rs3 | FEQ     |
10100   | 00/01/11 | src2     | src1  | **011**| pred rs3 | FNE     |
10100   | 00/01/11 | src2     | src1  | 001    | pred rs3 | FLT     |
10100   | 00/01/11 | src2     | src1  | 000    | pred rs3 | FLE     |
"""]]

Note (**TBD**): floating-point exceptions will need to be extended
to cater for multiple exceptions (and statuses of the same).  The
usual approach is to have an array of status codes and bit-fields,
and one exception, rather than throw separate exceptions for each
Vector element.

In Hwacha EECS-2015-262 Section 6.7.2 the following pseudocode is given
for predicated compare operations of function "cmp":

    for (int i=0; i<vl; ++i)
      if ([!]preg[p][i])
         preg[pd][i] = cmp(s1 ? vreg[rs1][i] : sreg[rs1],
                           s2 ? vreg[rs2][i] : sreg[rs2]);

With associated predication, vector-length adjustments and so on,
and temporarily ignoring bitwidth (which makes the comparisons more
complex), this becomes:

    if I/F == INT: # integer type cmp
        pred_enabled = int_pred_enabled # TODO: exception if not set!
        preg = int_pred_reg[rd]
        reg = int_regfile
    else:
        pred_enabled = fp_pred_enabled # TODO: exception if not set!
        preg = fp_pred_reg[rd]
        reg = fp_regfile

    s1 = CSRvectorlen[src1] > 1;
    s2 = CSRvectorlen[src2] > 1;
    for (int i=0; i<vl; ++i)
       preg[rs3][i] = cmp(s1 ? reg[src1+i] : reg[src1],
                          s2 ? reg[src2+i] : reg[src2]);

Notes:

* Predicated SIMD comparisons would break src1 and src2 further down
  into bitwidth-sized chunks (see Appendix "Bitwidth Virtual Register
  Reordering") setting Vector-Length times (number of SIMD elements) bits
  in Predicate Register rs3 as opposed to just Vector-Length bits.
* Predicated Branches do not actually have an adjustment to the Program
  Counter, so all of bits 25 through 30 in every case are not needed.
* There are plenty of reserved opcodes for which bits 25 through 30 could
  be put to good use if there is a suitable use-case.
* FEQ and FNE (and BEQ and BNE) are included in order to save one
  instruction having to invert the resultant predicate bitfield.
  FLT and FLE may be inverted to FGT and FGE if needed by swapping
  src1 and src2 (likewise the integer counterparts).

## Compressed Branch Instruction:

[[!table  data="""
15..13 | 12...10  | 9..7 | 6..5  | 4..2 | 1..0 | name |
funct3 | imm      | rs10 | imm   |      | op   |      |
3      | 3        | 3    | 2     |  3   | 2    |      |
C.BPR  | pred rs3 | src1 | I/F B | src2 | C1   |      |
110    | pred rs3 | src1 | I/F 0 | src2 | C1   | P.EQ |
111    | pred rs3 | src1 | I/F 0 | src2 | C1   | P.NE |
110    | pred rs3 | src1 | I/F 1 | src2 | C1   | P.LT |
111    | pred rs3 | src1 | I/F 1 | src2 | C1   | P.LE |
"""]]

Notes:

* Bits 5 13 14 and 15 make up the comparator type
* Bit 6 indicates whether to use integer or floating-point comparisons
* In both floating-point and integer cases there are four predication
  comparators: EQ/NEQ/LT/LE (with GT and GE being synthesised by inverting
  src1 and src2).

## LOAD / STORE Instructions

For full analysis of topological adaptation of RVV LOAD/STORE
see [[v_comparative_analysis]].  All three types (LD, LD.S and LD.X)
may be implicitly overloaded into the one base RV LOAD instruction,
and likewise for STORE.

Revised LOAD:

[[!table  data="""
31 | 30 | 29 25 | 24    20 | 19 15 | 14   12 | 11 7 | 6    0 |
imm[11:0]               |||| rs1   | funct3  | rd   | opcode |
1  | 1  |  5    | 5        | 5     | 3       | 5    | 7      |
?  | s  |  rs2  | imm[4:0] | base  | width   | dest | LOAD   |
"""]]

The exact same corresponding adaptation is also carried out on the single,
double and quad precision floating-point LOAD-FP and STORE-FP operations,
which fit the exact same instruction format.  Thus all three types
(unit, stride and indexed) may be fitted into FLW, FLD and FLQ,
as well as FSW, FSD and FSQ.

Notes:

* LOAD remains functionally (topologically) identical to RVV LOAD
  (for both integer and floating-point variants).
* Predication CSR-marking register is not explicitly shown in instruction, it's
  implicit based on the CSR predicate state for the rd (destination) register
* rs2, the source, may *also be marked as a vector*, which implicitly
  is taken to indicate "Indexed Load" (LD.X)
* Bit 30 indicates "element stride" or "constant-stride" (LD or LD.S)
* Bit 31 is reserved (ideas under consideration: auto-increment)
* **TODO**: include CSR SIMD bitwidth in the pseudo-code below.
* **TODO**: clarify where width maps to elsize

Pseudo-code (excludes CSR SIMD bitwidth for simplicity):

    if (unit-strided) stride = elsize;
    else stride = areg[as2]; // constant-strided

    pred_enabled = int_pred_enabled
    preg = int_pred_reg[rd]

    for (int i=0; i<vl; ++i)
      if (preg_enabled[rd] && [!]preg[i])
        for (int j=0; j<seglen+1; j++)
        {
          if CSRvectorised[rs2])
             offs = vreg[rs2][i]
          else
             offs = i*(seglen+1)*stride;
          vreg[rd+j][i] = mem[sreg[base] + offs + j*stride];
        }

Taking CSR (SIMD) bitwidth into account involves using the vector
length and register encoding according to the "Bitwidth Virtual Register
Reordering" scheme shown in the Appendix (see function "regoffs").

A similar instruction exists for STORE, with identical topological
translation of all features.  **TODO**

## Compressed LOAD / STORE Instructions

Compressed LOAD and STORE are of the same format, where bits 2-4 are
a src register instead of dest:

[[!table  data="""
15  13 | 12       10 | 9    7 | 6         5 | 4  2 | 1  0 |
funct3 | imm         | rs10   | imm         | rd0  | op   |
3      | 3           | 3      | 2           | 3    | 2    |
C.LW   | offset[5:3] | base   | offset[2|6] | dest | C0   |
"""]]

Unfortunately it is not possible to fit the full functionality
of vectorised LOAD / STORE into C.LD / C.ST: the "X" variants (Indexed)
require another operand (rs2) in addition to the operand width
(which is also missing), offset, base, and src/dest.

However a close approximation may be achieved by taking the top bit
of the offset in each of the five types of LD (and ST), reducing the
offset to 4 bits and utilising the 5th bit to indicate whether "stride"
is to be enabled.  In this way it is at least possible to introduce
that functionality.

(**TODO**: *assess whether the loss of one bit from offset is worth having
"stride" capability.*)

We also assume (including for the "stride" variant) that the "width"
parameter, which is missing, is derived and implicit, just as it is
with the standard Compressed LOAD/STORE instructions.  For C.LW, C.LD
and C.LQ, the width is implicitly 4, 8 and 16 respectively, whilst for
C.FLW and C.FLD the width is implicitly 4 and 8 respectively.

Interestingly we note that the Vectorised Simple-V variant of
LOAD/STORE (Compressed and otherwise), due to it effectively using the
standard register file(s), is the direct functional equivalent of
standard load-multiple and store-multiple instructions found in other
processors.

In Section 12.3 riscv-isa manual V2.3-draft it is noted the comments on
page 76, "For virtual memory systems some data accesses could be resident
in physical memory and some not".  The interesting question then arises:
how does RVV deal with the exact same scenario?
Expired U.S. Patent 5895501 (Filing Date Sep 3 1996) describes a method
of detecting early page / segmentation faults and adjusting the TLB
in advance, accordingly: other strategies are explored in the Appendix
Section "Virtual Memory Page Faults".

# CSRs <a name="csrs"></a>

There are a number of CSRs needed, which are used at the instruction
decode phase to re-interpret standard RV opcodes (a practice that has
precedent in the setting of MISA to enable / disable extensions).

* Integer Register N is Vector of length M: r(N) -> r(N..N+M-1)
* Integer Register N is of implicit bitwidth M (M=default,8,16,32,64)
* Floating-point Register N is Vector of length M: r(N) -> r(N..N+M-1)
* Floating-point Register N is of implicit bitwidth M (M=default,8,16,32,64)
* Integer Register N is a Predication Register (note: a key-value store)
* Vector Length CSR (VSETVL, VGETVL)

Notes:

* for the purposes of LOAD / STORE, Integer Registers which are
  marked as a Vector will result in a Vector LOAD / STORE.
* Vector Lengths are *not* the same as vsetl but are an integral part
  of vsetl.
* Actual vector length is *multipled* by how many blocks of length
  "bitwidth" may fit into an XLEN-sized register file.
* Predication is a key-value store due to the implicit referencing,
  as opposed to having the predicate register explicitly in the instruction.

## Predication CSR

The Predication CSR is a key-value store indicating whether, if a given
destination register (integer or floating-point) is referred to in an
instruction, it is to be predicated.  The first entry is whether predication
is enabled.  The second entry is whether the register index refers to a
floating-point or an integer register.  The third entry is the index
of that register which is to be predicated (if referred to).  The fourth entry
is the integer register that is treated as a bitfield, indexable by the
vector element index.

| RegNo | 6      | 5   | (4..0)  | (4..0)  |
| ----- | -      | -   | ------- | ------- |
| r0    | pren0  | i/f | regidx  | predidx |
| r1    | pren1  | i/f | regidx  | predidx |
| ..    | pren.. | i/f | regidx  | predidx |
| r15   | pren15 | i/f | regidx  | predidx |

The Predication CSR Table is a key-value store, so implementation-wise
it will be faster to turn the table around (maintain topologically
equivalent state):

    fp_pred_enabled[32];
    int_pred_enabled[32];
    for (i = 0; i < 16; i++)
       if CSRpred[i].pren:
          idx = CSRpred[i].regidx
          predidx = CSRpred[i].predidx
          if CSRpred[i].type == 0: # integer
            int_pred_enabled[idx] = 1
            int_pred_reg[idx] = predidx
          else:
            fp_pred_enabled[idx] = 1
            fp_pred_reg[idx] = predidx

So when an operation is to be predicated, it is the internal state that
is used.  In Section 6.4.2 of Hwacha's Manual (EECS-2015-262) the following
pseudo-code for operations is given, where p is the explicit (direct)
reference to the predication register to be used:

    for (int i=0; i<vl; ++i)
        if ([!]preg[p][i])
           (d ? vreg[rd][i] : sreg[rd]) =
            iop(s1 ? vreg[rs1][i] : sreg[rs1],
                s2 ? vreg[rs2][i] : sreg[rs2]); // for insts with 2 inputs

This instead becomes an *indirect* reference using the *internal* state
table generated from the Predication CSR key-value store:

    if type(iop) == INT:
        pred_enabled = int_pred_enabled
        preg = int_pred_reg[rd]
    else:
        pred_enabled = fp_pred_enabled
        preg = fp_pred_reg[rd]

    for (int i=0; i<vl; ++i)
        if (preg_enabled[rd] && [!]preg[i])
           (d ? vreg[rd][i] : sreg[rd]) =
            iop(s1 ? vreg[rs1][i] : sreg[rs1],
                s2 ? vreg[rs2][i] : sreg[rs2]); // for insts with 2 inputs

## MAXVECTORDEPTH

MAXVECTORDEPTH is the same concept as MVL in RVV.  However in Simple-V,
given that its primary (base, unextended) purpose is for 3D, Video and
other purposes (not requiring supercomputing capability), it makes sense
to limit MAXVECTORDEPTH to the regfile bitwidth (32 for RV32, 64 for RV64
and so on).

The reason for setting this limit is so that predication registers, when
marked as such, may fit into a single register as opposed to fanning out
over several registers.  This keeps the implementation a little simpler.
Note that RVV on top of Simple-V may choose to over-ride this decision.

## Vector-length CSRs

Vector lengths are interpreted as meaning "any instruction referring to
r(N) generates implicit identical instructions referring to registers
r(N+M-1) where M is the Vector Length".  Vector Lengths may be set to
use up to 16 registers in the register file.

One separate CSR table is needed for each of the integer and floating-point
register files:

| RegNo | (3..0) |
| ----- | ------ |
| r0    | vlen0  |
| r1    | vlen1  |
| ..    | vlen.. |
| r31   | vlen31 |

An array of 32 4-bit CSRs is needed (4 bits per register) to indicate
whether a register was, if referred to in any standard instructions,
implicitly to be treated as a vector.  A vector length of 1 indicates
that it is to be treated as a scalar.  Vector lengths of 0 are reserved.

Internally, implementations may choose to use the non-zero vector length
to set a bit-field per register, to be used in the instruction decode phase.
In this way any standard (current or future) operation involving
register operands may detect if the operation is to be vector-vector,
vector-scalar or scalar-scalar (standard) simply through a single
bit test.

Note that when using the "vsetl rs1, rs2" instruction (caveat: when the
bitwidth is specifically not set) it becomes:

    CSRvlength = MIN(MIN(CSRvectorlen[rs1], MAXVECTORDEPTH), rs2)

This is in contrast to RVV:

    CSRvlength = MIN(MIN(rs1, MAXVECTORDEPTH), rs2)

## Element (SIMD) bitwidth CSRs

Element bitwidths may be specified with a per-register CSR, and indicate
how a register (integer or floating-point) is to be subdivided.

| RegNo | (2..0) |
| ----- | ------ |
| r0    | vew0   |
| r1    | vew1   |
| ..    | vew..  |
| r31   | vew31  |

vew may be one of the following (giving a table "bytestable", used below):

| vew | bitwidth |
| --- | -------- |
| 000 | default  |
| 001 | 8        |
| 010 | 16       |
| 011 | 32       |
| 100 | 64       |
| 101 | 128      |
| 110 | rsvd     |
| 111 | rsvd     |

Extending this table (with extra bits) is covered in the section
"Implementing RVV on top of Simple-V".

Note that when using the "vsetl rs1, rs2" instruction, taking bitwidth
into account, it becomes:

    vew = CSRbitwidth[rs1]
    if (vew == 0)
        bytesperreg = (XLEN/8) # or FLEN as appropriate
    else:
        bytesperreg = bytestable[vew] # 1 2 4 8 16
    simdmult = (XLEN/8) / bytesperreg # or FLEN as appropriate
    vlen = CSRvectorlen[rs1] * simdmult
    CSRvlength = MIN(MIN(vlen, MAXVECTORDEPTH), rs2)

The reason for multiplying the vector length by the number of SIMD elements
(in each individual register) is so that each SIMD element may optionally be
predicated.

An example of how to subdivide the register file when bitwidth != default
is given in the section "Bitwidth Virtual Register Reordering".

# Exceptions

> What does an ADD of two different-sized vectors do in simple-V?

* if the two source operands are not the same, throw an exception.
* if the destination operand is also a vector, and the source is longer
  than the destination, throw an exception.

> And what about instructions like JALR? 
> What does jumping to a vector do?

* Throw an exception.  Whether that actually results in spawning threads
  as part of the trap-handling remains to be seen.

# Impementing V on top of Simple-V

With Simple-V converting the original RVV draft concept-for-concept
from explicit opcodes to implicit overloading of existing RV Standard
Extensions, certain features were (deliberately) excluded that need
to be added back in for RVV to reach its full potential.  This is
made slightly complicated by the fact that RVV itself has two
levels: Base and reserved future functionality.

* Representation Encoding is entirely left out of Simple-V in favour of
  implicitly taking the exact (explicit) meaning from RV Standard Extensions.
* VCLIP and VCLIPI do not have corresponding RV Standard Extension
  opcodes (and are the only such operations).
* Extended Element bitwidths (1 through to 24576 bits) were left out
  of Simple-V as, again, there is no corresponding RV Standard Extension
  that covers anything even below 32-bit operands.
* Polymorphism was entirely left out of Simple-V due to the inherent
  complexity of automatic type-conversion.
* Vector Register files were specifically left out of Simple-V in favour
  of fitting on top of the integer and floating-point files.  An
  "RVV re-retro-fit" needs to be able to mark (implicitly marked)
  registers as being actually in a separate *vector* register file.
* Fortunately in RVV (Draft 0.4, V2.3-Draft), the "base" vector
  register file size is 5 bits (32 registers), whilst the "Extended"
  variant of RVV specifies 8 bits (256 registers) and has yet to
  be published.
* One big difference: Sections 17.12 and 17.17, there are only two possible
  predication registers in RVV "Base".  Through the "indirect" method,
  Simple-V provides a key-value CSR table that allows (arbitrarily)
  up to 16 (TBD) of either the floating-point or integer registers to
  be marked as "predicated" (key), and if so, which integer register to
  use as the predication mask (value).
  
**TODO**

# Implementing P (renamed to DSP) on top of Simple-V

* Implementors indicate chosen bitwidth support in Vector-bitwidth CSR
  (caveat: anything not specified drops through to software-emulation / traps)
* TODO

# Appendix

## V-Extension to Simple-V Comparative Analysis

This section has been moved to its own page [[v_comparative_analysis]]

## P-Ext ISA

This section has been moved to its own page [[p_comparative_analysis]]

## Comparison of "Traditional" SIMD, Alt-RVP, Simple-V and RVV Proposals <a name="parallelism_comparisons"></a>

This section compares the various parallelism proposals as they stand,
including traditional SIMD, in terms of features, ease of implementation,
complexity, flexibility, and die area.

### [[alt_rvp]]

Primary benefit of Alt-RVP is the simplicity with which parallelism
may be introduced (effective multiplication of regfiles and associated ALUs).

* plus: the simplicity of the lanes (combined with the regularity of
  allocating identical opcodes multiple independent registers) meaning
  that SRAM or 2R1W can be used for entire regfile (potentially).
* minus: a more complex instruction set where the parallelism is much
  more explicitly directly specified in the instruction and
* minus: if you *don't* have an explicit instruction (opcode) and you
  need one, the only place it can be added is... in the vector unit and
* minus: opcode functions (and associated ALUs) duplicated in Alt-RVP are
  not useable or accessible in other Extensions.
* plus-and-minus: Lanes may be utilised for high-speed context-switching
  but with the down-side that they're an all-or-nothing part of the Extension.
  No Alt-RVP: no fast register-bank switching.
* plus: Lane-switching would mean that complex operations not suited to
  parallelisation can be carried out, followed by further parallel Lane-based
  work, without moving register contents down to memory (and back)
* minus: Access to registers across multiple lanes is challenging. "Solution"
  is to drop data into memory and immediately back in again (like MMX).

### Simple-V

Primary benefit of Simple-V is the OO abstraction of parallel principles
from actual (internal) parallel hardware.  It's an API in effect that's
designed to be slotted in to an existing implementation (just after
instruction decode) with minimum disruption and effort.

* minus: the complexity of having to use register renames, OoO, VLIW,
  register file cacheing, all of which has been done before but is a
  pain
* plus: transparent re-use of existing opcodes as-is just indirectly
  saying "this register's now a vector" which
* plus: means that future instructions also get to be inherently
  parallelised because there's no "separate vector opcodes"
* plus: Compressed instructions may also be (indirectly) parallelised
* minus: the indirect nature of Simple-V means that setup (setting
  a CSR register to indicate vector length, a separate one to indicate
  that it is a predicate register and so on) means a little more setup
  time than Alt-RVP or RVV's "direct and within the (longer) instruction"
  approach.
* plus: shared register file meaning that, like Alt-RVP, complex
  operations not suited to parallelisation may be carried out interleaved
  between parallelised instructions *without* requiring data to be dropped
  down to memory and back (into a separate vectorised register engine).
* plus-and-maybe-minus: re-use of integer and floating-point 32-wide register
  files means that huge parallel workloads would use up considerable
  chunks of the register file.  However in the case of RV64 and 32-bit
  operations, that effectively means 64 slots are available for parallel
  operations.
* plus: inherent parallelism (actual parallel ALUs) doesn't actually need to
  be added, yet the instruction opcodes remain unchanged (and still appear
  to be parallel).  consistent "API" regardless of actual internal parallelism:
  even an in-order single-issue implementation with a single ALU would still
  appear to have parallel vectoristion.
* hard-to-judge: if actual inherent underlying ALU parallelism is added it's
  hard to say if there would be pluses or minuses (on die area).  At worse it
  would be "no worse" than existing register renaming, OoO, VLIW and register
  file cacheing schemes.

### RVV (as it stands, Draft 0.4 Section 17, RISC-V ISA V2.3-Draft)

RVV is extremely well-designed and has some amazing features, including
2D reorganisation of memory through LOAD/STORE "strides".

* plus: regular predictable workload means that implementations may
  streamline effects on L1/L2 Cache.
* plus: regular and clear parallel workload also means that lanes
  (similar to Alt-RVP) may be used as an implementation detail,
  using either SRAM or 2R1W registers.
* plus: separate engine with no impact on the rest of an implementation
* minus: separate *complex* engine with no RTL (ALUs, Pipeline stages) reuse
  really feasible.
* minus: no ISA abstraction or re-use either: additions to other Extensions
  do not gain parallelism, resulting in prolific duplication of functionality
  inside RVV *and out*.
* minus: when operations require a different approach (scalar operations
  using the standard integer or FP regfile) an entire vector must be
  transferred out to memory, into standard regfiles, then back to memory,
  then back to the vector unit, this to occur potentially multiple times.
* minus: will never fit into Compressed instruction space (as-is.  May
  be able to do so if "indirect" features of Simple-V are partially adopted).
* plus-and-slight-minus: extended variants may address up to 256
  vectorised registers (requires 48/64-bit opcodes to do it).
* minus-and-partial-plus: separate engine plus complexity increases
  implementation time and die area, meaning that adoption is likely only
  to be in high-performance specialist supercomputing (where it will
  be absolutely superb).

### Traditional SIMD

The only really good things about SIMD are how easy it is to implement and
get good performance.  Unfortunately that makes it quite seductive...

* plus: really straightforward, ALU basically does several packed operations
  at once.  Parallelism is inherent at the ALU, making the addition of
  SIMD-style parallelism an easy decision that has zero significant impact
  on the rest of any given architectural design and layout.
* plus (continuation): SIMD in simple in-order single-issue designs can
  therefore result in superb throughput, easily achieved even with a very
  simple execution model.
* minus: ridiculously complex setup and corner-cases that disproportionately
  increase instruction count on what would otherwise be a "simple loop",
  should the number of elements in an array not happen to exactly match
  the SIMD group width.
* minus: getting data usefully out of registers (if separate regfiles
  are used) means outputting to memory and back.
* minus: quite a lot of supplementary instructions for bit-level manipulation
  are needed in order to efficiently extract (or prepare) SIMD operands.
* minus: MASSIVE proliferation of ISA both in terms of opcodes in one
  dimension and parallelism (width): an at least O(N^2) and quite probably
  O(N^3) ISA proliferation that often results in several thousand
  separate instructions.  all requiring separate and distinct corner-case
  algorithms!
* minus: EVEN BIGGER proliferation of SIMD ISA if the functionality of
  8, 16, 32 or 64-bit reordering is built-in to the SIMD instruction.
  For example: add (high|low) 16-bits of r1 to (low|high) of r2 requires
  four separate and distinct instructions: one for (r1:low r2:high),
  one for (r1:high r2:low), one for (r1:high r2:high) and one for
  (r1:low r2:low) *per function*.
* minus: EVEN BIGGER proliferation of SIMD ISA if there is a mismatch
  between operand and result bit-widths.  In combination with high/low
  proliferation the situation is made even worse.
* minor-saving-grace: some implementations *may* have predication masks
  that allow control over individual elements within the SIMD block.

## Comparison *to* Traditional SIMD: Alt-RVP, Simple-V and RVV Proposals <a name="simd_comparison"></a>

This section compares the various parallelism proposals as they stand,
*against* traditional SIMD as opposed to *alongside* SIMD.  In other words,
the question is asked "How can each of the proposals effectively implement
(or replace) SIMD, and how effective would they be"?

### [[alt_rvp]]

* Alt-RVP would not actually replace SIMD but would augment it: just as with
  a SIMD architecture where the ALU becomes responsible for the parallelism,
  Alt-RVP ALUs would likewise be so responsible... with *additional*
  (lane-based) parallelism on top.
* Thus at least some of the downsides of SIMD ISA O(N^3) proliferation by
  at least one dimension are avoided (architectural upgrades introducing
  128-bit then 256-bit then 512-bit variants of the exact same 64-bit
  SIMD block)
* Thus, unfortunately, Alt-RVP would suffer the same inherent proliferation
  of instructions as SIMD, albeit not quite as badly (due to Lanes).
* In the same discussion for Alt-RVP, an additional proposal was made to
  be able to subdivide the bits of each register lane (columns) down into
  arbitrary bit-lengths (RGB 565 for example).
* A recommendation was given instead to make the subdivisions down to 32-bit,
  16-bit or even 8-bit, effectively dividing the registerfile into
  Lane0(H), Lane0(L), Lane1(H) ... LaneN(L) or further.  If inter-lane
  "swapping" instructions were then introduced, some of the disadvantages
  of SIMD could be mitigated.

### RVV

* RVV is designed to replace SIMD with a better paradigm: arbitrary-length
  parallelism.
* However whilst SIMD is usually designed for single-issue in-order simple
  DSPs with a focus on Multimedia (Audio, Video and Image processing),
  RVV's primary focus appears to be on Supercomputing: optimisation of
  mathematical operations that fit into the OpenCL space.
* Adding functions (operations) that would normally fit (in parallel)
  into a SIMD instruction requires an equivalent to be added to the
  RVV Extension, if one does not exist.  Given the specialist nature of
  some SIMD instructions (8-bit or 16-bit saturated or halving add),
  this possibility seems extremely unlikely to occur, even if the
  implementation overhead of RVV were acceptable (compared to
  normal SIMD/DSP-style single-issue in-order simplicity).

### Simple-V

* Simple-V borrows hugely from RVV as it is intended to be easy to
  topologically transplant every single instruction from RVV (as
  designed) into Simple-V equivalents, with *zero loss of functionality
   or capability*.
* With the "parallelism" abstracted out, a hypothetical SIMD-less "DSP"
  Extension which contained the basic primitives (non-parallelised
  8, 16 or 32-bit SIMD operations) inherently *become* parallel,
  automatically.
* Additionally, standard operations (ADD, MUL) that would normally have
  to have special SIMD-parallel opcodes added need no longer have *any*
  of the length-dependent variants (2of 32-bit ADDs in a 64-bit register,
  4of 32-bit ADDs in a 128-bit register) because Simple-V takes the
  *standard* RV opcodes (present and future) and automatically parallelises
  them.
* By inheriting the RVV feature of arbitrary vector-length, then just as
  with RVV the corner-cases and ISA proliferation of SIMD is avoided.
* Whilst not entirely finalised, registers are expected to be
  capable of being subdivided down to an implementor-chosen bitwidth
  in the underlying hardware (r1 becomes r1[31..24] r1[23..16] r1[15..8]
  and r1[7..0], or just r1[31..16] r1[15..0]) where implementors can
  choose to have separate independent 8-bit ALUs or dual-SIMD 16-bit
  ALUs that perform twin 8-bit operations as they see fit, or anything
  else including no subdivisions at all.
* Even though implementors have that choice even to have full 64-bit
  (with RV64) SIMD, they *must* provide predication that transparently
  switches off appropriate units on the last loop, thus neatly fitting
  underlying SIMD ALU implementations *into* the arbitrary vector-length
  RVV paradigm, keeping the uniform consistent API that is a key strategic
  feature of Simple-V.
* With Simple-V fitting into the standard register files, certain classes
  of SIMD operations such as High/Low arithmetic (r1[31..16] + r2[15..0])
  can be done by applying *Parallelised* Bit-manipulation operations
  followed by parallelised *straight* versions of element-to-element
  arithmetic operations, even if the bit-manipulation operations require
  changing the bitwidth of the "vectors" to do so.  Predication can
  be utilised to skip high words (or low words) in source or destination.
* In essence, the key downside of SIMD - massive duplication of
  identical functions over time as an architecture evolves from 32-bit
  wide SIMD all the way up to 512-bit, is avoided with Simple-V, through
  vector-style parallelism being dropped on top of 8-bit or 16-bit
  operations, all the while keeping a consistent ISA-level "API" irrespective
  of implementor design choices (or indeed actual implementations).

### Example Instruction translation: <a name="example_translation"></a>

Instructions "ADD r2 r4 r4" would result in three instructions being
generated and placed into the FIFO:

* ADD r2 r4 r4
* ADD r2 r5 r5
* ADD r2 r6 r6

## Example of vector / vector, vector / scalar, scalar / scalar => vector add

    register CSRvectorlen[XLEN][4]; # not quite decided yet about this one...
    register CSRpredicate[XLEN][4]; # 2^4 is max vector length
    register CSRreg_is_vectorised[XLEN]; # just for fun support scalars as well
    register x[32][XLEN];

    function op_add(rd, rs1, rs2, predr)
    {
       /* note that this is ADD, not PADD */
       int i, id, irs1, irs2;
       # checks CSRvectorlen[rd] == CSRvectorlen[rs] etc. ignored
       # also destination makes no sense as a scalar but what the hell...
       for (i = 0, id=0, irs1=0, irs2=0; i<CSRvectorlen[rd]; i++)
          if (CSRpredicate[predr][i]) # i *think* this is right...
             x[rd+id] <= x[rs1+irs1] + x[rs2+irs2];
          # now increment the idxs
          if (CSRreg_is_vectorised[rd]) # bitfield check rd, scalar/vector?
             id += 1;
          if (CSRreg_is_vectorised[rs1]) # bitfield check rs1, scalar/vector?
             irs1 += 1;
          if (CSRreg_is_vectorised[rs2]) # bitfield check rs2, scalar/vector?
             irs2 += 1;
    }

## Retro-fitting Predication into branch-explicit ISA <a name="predication_retrofit"></a>

One of the goals of this parallelism proposal is to avoid instruction
duplication.  However, with the base ISA having been designed explictly
to *avoid* condition-codes entirely, shoe-horning predication into it
bcomes quite challenging.

However what if all branch instructions, if referencing a vectorised
register, were instead given *completely new analogous meanings* that
resulted in a parallel bit-wise predication register being set?  This
would have to be done for both C.BEQZ and C.BNEZ, as well as BEQ, BNE,
BLT and BGE.

We might imagine that FEQ, FLT and FLT would also need to be converted,
however these are effectively *already* in the precise form needed and
do not need to be converted *at all*!  The difference is that FEQ, FLT
and FLE *specifically* write a 1 to an integer register if the condition
holds, and 0 if not.  All that needs to be done here is to say, "if
the integer register is tagged with a bit that says it is a predication
register, the **bit** in the integer register is set based on the
current vector index" instead.

There is, in the standard Conditional Branch instruction, more than
adequate space to interpret it in a similar fashion:

[[!table  data="""
  31    |30 ..... 25 |24 ... 20 | 19 ... 15 | 14 ...... 12 | 11 .......  8 |      7  | 6 ....... 0 |
imm[12] | imm[10:5]  |        rs2 |     rs1 |       funct3 |      imm[4:1] | imm[11] |    opcode   |
 1      |        6   |      5   |      5    |       3      |     4         |  1      |   7         |
   offset[12,10:5]  ||    src2  |    src1   |  BEQ         |    offset[11,4:1]      || BRANCH      |
"""]]

This would become:

[[!table  data="""
31      | 30 .. 25 |24 ... 20 | 19 15 | 14  12 | 11 ..  8 | 7       | 6 ... 0 |
imm[12] | imm[10:5]| rs2      | rs1   | funct3 | imm[4:1] | imm[11] | opcode  |
1       | 6        | 5        | 5     | 3      | 4             | 1  | 7       |
reserved          || src2     | src1  | BEQ    | predicate rs3     || BRANCH  |
"""]]

Similarly the C.BEQZ and C.BNEZ instruction format may be retro-fitted,
with the interesting side-effect that there is space within what is presently
the "immediate offset" field to reinterpret that to add in not only a bit
field to distinguish between floating-point compare and integer compare,
not only to add in a second source register, but also use some of the bits as
a predication target as well.

[[!table  data="""
15 ...... 13 | 12 ...........  10 | 9..... 7 | 6 ................. 2 | 1 .. 0 |
   funct3    |       imm          |   rs10   |         imm           |   op   |
      3      |         3          |    3     |           5           |   2    |
   C.BEQZ    |   offset[8,4:3]    |   src    |   offset[7:6,2:1,5]   |   C1   |
"""]]

Now uses the CS format:

[[!table  data="""
15 ...... 13 | 12 ...........  10 | 9..... 7 | 6 .. 5 | 4......... 2 | 1 .. 0 |
   funct3    |       imm          |   rs10   |  imm   |              |   op   |
      3      |         3          |    3     |  2     |  3           |   2    |
   C.BEQZ    |   predicate rs3    |   src1   |  I/F B | src2         |   C1   |
"""]]

Bit 6 would be decoded as "operation refers to Integer or Float" including
interpreting src1 and src2 accordingly as outlined in Table 12.2 of the
"C" Standard, version 2.0,
whilst Bit 5 would allow the operation to be extended, in combination with
funct3 = 110 or 111: a combination of four distinct (predicated) comparison
operators.  In both floating-point and integer cases those could be
EQ/NEQ/LT/LE (with GT and GE being synthesised by inverting src1 and src2).

## Register reordering <a name="register_reordering"></a>

### Register File

| Reg Num | Bits |
| ------- | ---- |
| r0 | (32..0) |
| r1 | (32..0) |
| r2 | (32..0) |
| r3 | (32..0) |
| r4 | (32..0) |
| r5 | (32..0) |
| r6 | (32..0) |
| r7 | (32..0) |
| .. | (32..0) |
| r31| (32..0) |

### Vectorised CSR

May not be an actual CSR: may be generated from Vector Length CSR:
single-bit is less burdensome on instruction decode phase.

| 7 | 6 | 5 | 4 | 3 | 2 | 1 | 0 |
| - | - | - | - | - | - | - | - |
| 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 |

### Vector Length CSR

| Reg Num | (3..0) |
| ------- | ---- |
| r0 | 2 |
| r1 | 0 |
| r2 | 1 |
| r3 | 1 |
| r4 | 3 |
| r5 | 0 |
| r6 | 0 |
| r7 | 1 |

### Virtual Register Reordering

This example assumes the above Vector Length CSR table

| Reg Num | Bits (0) | Bits (1) | Bits (2) |
| ------- | -------- | -------- | -------- |
| r0 | (32..0) | (32..0) |
| r2 | (32..0) |
| r3 | (32..0) |
| r4 | (32..0) | (32..0) | (32..0) |
| r7 | (32..0) |

### Bitwidth Virtual Register Reordering

This example goes a little further and illustrates the effect that a
bitwidth CSR has been set on a register.  Preconditions:

* RV32 assumed
* CSRintbitwidth[2] = 010 # integer r2 is 16-bit
* CSRintvlength[2] = 3 # integer r2 is a vector of length 3
* vsetl rs1, 5 # set the vector length to 5

This is interpreted as follows:

* Given that the context is RV32, ELEN=32.
* With ELEN=32 and bitwidth=16, the number of SIMD elements is 2
* Therefore the actual vector length is up to *six* elements
* However vsetl sets a length 5 therefore the last "element" is skipped

So when using an operation that uses r2 as a source (or destination)
the operation is carried out as follows:

* 16-bit operation on r2(15..0) - vector element index 0
* 16-bit operation on r2(31..16) - vector element index 1
* 16-bit operation on r3(15..0) - vector element index 2
* 16-bit operation on r3(31..16) - vector element index 3
* 16-bit operation on r4(15..0) - vector element index 4
* 16-bit operation on r4(31..16) **NOT** carried out due to length being 5

Predication has been left out of the above example for simplicity, however
predication is ANDed with the latter stages (vsetl not equal to maximum
capacity).

Note also that it is entirely an implementor's choice as to whether to have
actual separate ALUs down to the minimum bitwidth, or whether to have something
more akin to traditional SIMD (at any level of subdivision: 8-bit SIMD
operations carried out 32-bits at a time is perfectly acceptable, as is
8-bit SIMD operations carried out 16-bits at a time requiring two ALUs).
Regardless of the internal parallelism choice, *predication must
still be respected*, making Simple-V in effect the "consistent public API".

vew may be one of the following (giving a table "bytestable", used below):

| vew | bitwidth |
| --- | -------- |
| 000 | default  |
| 001 | 8        |
| 010 | 16       |
| 011 | 32       |
| 100 | 64       |
| 101 | 128      |
| 110 | rsvd     |
| 111 | rsvd     |

Pseudocode for vector length taking CSR SIMD-bitwidth into account:

    vew = CSRbitwidth[rs1]
    if (vew == 0)
        bytesperreg = (XLEN/8) # or FLEN as appropriate
    else:
        bytesperreg = bytestable[vew] # 1 2 4 8 16
    simdmult = (XLEN/8) / bytesperreg # or FLEN as appropriate
    vlen = CSRvectorlen[rs1] * simdmult

To index an element in a register rnum where the vector element index is i:

    function regoffs(rnum, i):
        regidx = floor(i / simdmult)  # integer-div rounded down
        byteidx = i % simdmult        # integer-remainder
        return rnum + regidx,         # actual real register
               byteidx * 8,           # low
               byteidx * 8 + (vew-1), # high

### Insights

SIMD register file splitting still to consider.  For RV64, benefits of doubling
(quadrupling in the case of Half-Precision IEEE754 FP) the apparent
size of the floating point register file to 64 (128 in the case of HP)
seem pretty clear and worth the complexity.

64 virtual 32-bit F.P. registers and given that 32-bit FP operations are
done on 64-bit registers it's not so conceptually difficult.  May even
be achieved by *actually* splitting the regfile into 64 virtual 32-bit
registers such that a 64-bit FP scalar operation is dropped into (r0.H
r0.L) tuples.  Implementation therefore hidden through register renaming.

Implementations intending to introduce VLIW, OoO and parallelism
(even without Simple-V) would then find that the instructions are
generated quicker (or in a more compact fashion that is less heavy
on caches).  Interestingly we observe then that Simple-V is about
"consolidation of instruction generation", where actual parallelism
of underlying hardware is an implementor-choice that could just as
equally be applied *without* Simple-V even being implemented.

## Analysis of CSR decoding on latency <a name="csr_decoding_analysis"></a>

It could indeed have been logically deduced (or expected), that there
would be additional decode latency in this proposal, because if
overloading the opcodes to have different meanings, there is guaranteed
to be some state, some-where, directly related to registers.

There are several cases:

* All operands vector-length=1 (scalars), all operands
  packed-bitwidth="default": instructions are passed through direct as if
  Simple-V did not exist.  Simple-V is, in effect, completely disabled.
* At least one operand vector-length > 1, all operands
  packed-bitwidth="default": any parallel vector ALUs placed on "alert",
  virtual parallelism looping may be activated.
* All operands vector-length=1 (scalars), at least one
  operand packed-bitwidth != default: degenerate case of SIMD,
  implementation-specific complexity here (packed decode before ALUs or
  *IN* ALUs)
* At least one operand vector-length > 1, at least one operand
  packed-bitwidth != default: parallel vector ALUs (if any)
  placed on "alert", virtual parallelsim looping may be activated,
  implementation-specific SIMD complexity kicks in (packed decode before
  ALUs or *IN* ALUs).

Bear in mind that the proposal includes that the decision whether
to parallelise in hardware or whether to virtual-parallelise (to
dramatically simplify compilers and also not to run into the SIMD
instruction proliferation nightmare) *or* a transprent combination
of both, be done on a *per-operand basis*, so that implementors can
specifically choose to create an application-optimised implementation
that they believe (or know) will sell extremely well, without having
"Extra Standards-Mandated Baggage" that would otherwise blow their area
or power budget completely out the window.

Additionally, two possible CSR schemes have been proposed, in order to
greatly reduce CSR space:

* per-register CSRs (vector-length and packed-bitwidth)
* a smaller number of CSRs with the same information but with an *INDEX*
  specifying WHICH register in one of three regfiles (vector, fp, int)
  the length and bitwidth applies to.

(See "CSR vector-length and CSR SIMD packed-bitwidth" section for details)

In addition, LOAD/STORE has its own associated proposed CSRs that
mirror the STRIDE (but not yet STRIDE-SEGMENT?) functionality of
V (and Hwacha).

Also bear in mind that, for reasons of simplicity for implementors,
I was coming round to the idea of permitting implementors to choose
exactly which bitwidths they would like to support in hardware and which
to allow to fall through to software-trap emulation.

So the question boils down to:

* whether either (or both) of those two CSR schemes have significant
  latency that could even potentially require an extra pipeline decode stage
* whether there are implementations that can be thought of which do *not*
  introduce significant latency
* whether it is possible to explicitly (through quite simply
  disabling Simple-V-Ext) or implicitly (detect the case all-vlens=1,
  all-simd-bitwidths=default) switch OFF any decoding, perhaps even to
  the extreme of skipping an entire pipeline stage (if one is needed)
* whether packed bitwidth and associated regfile splitting is so complex
  that it should definitely, definitely be made mandatory that implementors
  move regfile splitting into the ALU, and what are the implications of that
* whether even if that *is* made mandatory, is software-trapped
  "unsupported bitwidths" still desirable, on the basis that SIMD is such
  a complete nightmare that *even* having a software implementation is
  better, making Simple-V have more in common with a software API than
  anything else.

Whilst the above may seem to be severe minuses, there are some strong
pluses:

* Significant reduction of V's opcode space: over 85%.
* Smaller reduction of P's opcode space: around 10%.
* The potential to use Compressed instructions in both Vector and SIMD
  due to the overloading of register meaning (implicit vectorisation,
  implicit packing)
* Not only present but also future extensions automatically gain parallelism.
* Already mentioned but worth emphasising: the simplification to compiler
  writers and assembly-level writers of having the same consistent ISA
  regardless of whether the internal level of parallelism (number of
  parallel ALUs) is only equal to one ("virtual" parallelism), or is
  greater than one, should not be underestimated.

## Reducing Register Bank porting

This looks quite reasonable.
<https://www.princeton.edu/~rblee/ELE572Papers/MultiBankRegFile_ISCA2000.pdf>

The main details are outlined on page 4.  They propose a 2-level register
cache hierarchy, note that registers are typically only read once, that
you never write back from upper to lower cache level but always go in a
cycle lower -> upper -> ALU -> lower, and at the top of page 5 propose
a scheme where you look ahead by only 2 instructions to determine which
registers to bring into the cache.

The nice thing about a vector architecture is that you *know* that
*even more* registers are going to be pulled in: Hwacha uses this fact
to optimise L1/L2 cache-line usage (avoid thrashing), strangely enough
by *introducing* deliberate latency into the execution phase.

## Overflow registers in combination with predication

**TODO**: propose overflow registers be actually one of the integer regs
(flowing to multiple regs).

**TODO**: propose "mask" (predication) registers likewise.  combination with
standard RV instructions and overflow registers extremely powerful, see
Aspex ASP.

When integer overflow is stored in an easily-accessible bit (or another
register), parallelisation turns this into a group of bits which can
potentially be interacted with in predication, in interesting and powerful
ways.  For example, by taking the integer-overflow result as a predication
field and shifting it by one, a predicated vectorised "add one" can emulate
"carry" on arbitrary (unlimited) length addition.

However despite RVV having made room for floating-point exceptions, neither
RVV nor base RV have taken integer-overflow (carry) into account, which
makes proposing it quite challenging given that the relevant (Base) RV
sections are frozen.  Consequently it makes sense to forgo this feature.

## Virtual Memory page-faults on LOAD/STORE


### Notes from conversations

> I was going through the C.LOAD / C.STORE section 12.3 of V2.3-Draft
> riscv-isa-manual in order to work out how to re-map RVV onto the standard
> ISA, and came across an interesting comments at the bottom of pages 75
> and 76:

> "   A common mechanism used in other ISAs to further reduce save/restore
> code size is load- multiple and store-multiple instructions. "

> Fascinatingly, due to Simple-V proposing to use the *standard* register
> file, both C.LOAD / C.STORE *and* LOAD / STORE would in effect be exactly
> that: load-multiple and store-multiple instructions.  Which brings us
> on to this comment:

> "For virtual memory systems, some data accesses could be resident in
> physical memory and
>   some could not, which requires a new restart mechanism for partially
> executed instructions."

> Which then of course brings us to the interesting question: how does RVV
> cope with the scenario when, particularly with LD.X (Indexed / indirect
> loads), part-way through the loading a page fault occurs?

> Has this been noted or discussed before?

For applications-class platforms, the RVV exception model is
element-precise (that is, if an exception occurs on element j of a
vector instruction, elements 0..j-1 have completed execution and elements
j+1..vl-1 have not executed).

Certain classes of embedded platforms where exceptions are always fatal
might choose to offer resumable/swappable interrupts but not precise
exceptions.


> Is RVV designed in any way to be re-entrant?

Yes.


> What would the implications be for instructions that were in a FIFO at
> the time, in out-of-order and VLIW implementations, where partial decode
> had taken place?

The usual bag of tricks for maintaining precise exceptions applies to
vector machines as well.  Register renaming makes the job easier, and
it's relatively cheaper for vectors, since the control cost is amortized
over longer registers.


> Would it be reasonable at least to say *bypass* (and freeze) the
> instruction FIFO (drop down to a single-issue execution model temporarily)
> for the purposes of executing the instructions in the interrupt (whilst
> setting up the VM page), then re-continue the instruction with all
> state intact?

This approach has been done successfully, but it's desirable to be
able to swap out the vector unit state to support context switches on
exceptions that result in long-latency I/O.


> Or would it be better to switch to an entirely separate secondary
> hyperthread context?

> Does anyone have any ideas or know if there is any academic literature
> on solutions to this problem?

The Vector VAX offered imprecise but restartable and swappable exceptions:
http://mprc.pku.edu.cn/~liuxianhua/chn/corpus/Notes/articles/isca/1990/VAX%20vector%20architecture.pdf

Sec. 4.6 of Krste's dissertation assesses some of
the tradeoffs and references a bunch of related work:
http://people.eecs.berkeley.edu/~krste/thesis.pdf


----

Started reading section 4.6 of Krste's thesis, noted the "IEE85 F.P
exceptions" and thought, "hmmm that could go into a CSR, must re-read
the section on FP state CSRs in RVV 0.4-Draft again" then i suddenly
thought, "ah ha!  what if the memory exceptions were, instead of having
an immediate exception thrown, were simply stored in a type of predication
bit-field with a flag "error this element failed"?

Then, *after* the vector load (or store, or even operation) was
performed, you could *then* raise an exception, at which point it
would be possible (yes in software... I know....) to go "hmmm, these
indexed operations didn't work, let's get them into memory by triggering
page-loads", then *re-run the entire instruction* but this time with a
"memory-predication CSR" that stops the already-performed operations
(whether they be loads, stores or an arithmetic / FP operation) from
being carried out a second time.

This theoretically could end up being done multiple times in an SMP
environment, and also for LD.X there would be the remote outside annoying
possibility that the indexed memory address could end up being modified.

The advantage would be that the order of execution need not be
sequential, which potentially could have some big advantages.
Am still thinking through the implications as any dependent operations
(particularly ones already decoded and moved into the execution FIFO)
would still be there (and stalled).  hmmm.

----

    > > # assume internal parallelism of 8 and MAXVECTORLEN of 8
    > > VSETL r0, 8
    > > FADD x1, x2, x3
    >
    > > x3[0]: ok
    > > x3[1]: exception
    > > x3[2]: ok
    > > ...
    > > ...
    > > x3[7]: ok
    >
    > > what happens to result elements 2-7?  those may be *big* results
    > > (RV128)
    > > or in the RVV-Extended may be arbitrary bit-widths far greater.
    >
    >  (you replied:)
    >
    > Thrown away.

discussion then led to the question of OoO architectures 

> The costs of the imprecise-exception model are greater than the benefit. 
> Software doesn't want to cope with it.  It's hard to debug.  You can't
> migrate state between different microarchitectures--unless you force all
> implementations to support the same imprecise-exception model, which would
> greatly limit implementation flexibility.  (Less important, but still
> relevant, is that the imprecise model increases the size of the context
> structure, as the microarchitectural guts have to be spilled to memory.)


## Implementation Paradigms

TODO: assess various implementation paradigms.  These are listed roughly
in order of simplicity (minimum compliance, for ultra-light-weight
embedded systems or to reduce design complexity and the burden of
design implementation and compliance, in non-critical areas), right the
way to high-performance systems.

* Full (or partial) software-emulated (via traps): full support for CSRs
  required, however when a register is used that is detected (in hardware)
  to be vectorised, an exception is thrown.
* Single-issue In-order, reduced pipeline depth (traditional SIMD / DSP)
* In-order 5+ stage pipelines with instruction FIFOs and mild register-renaming
* Out-of-order with instruction FIFOs and aggressive register-renaming
* VLIW

Also to be taken into consideration:

* "Virtual" vectorisation: single-issue loop, no internal ALU parallelism
* Comphrensive vectorisation: FIFOs and internal parallelism
* Hybrid Parallelism

# TODO Research

> For great floating point DSPs check TI’s C3x, C4X, and C6xx DSPs

Idea: basic simple butterfly swap on a few element indices, primarily targetted
at SIMD / DSP.  High-byte low-byte swapping, high-word low-word swapping,
perhaps allow reindexing of permutations up to 4 elements?  8?  Reason:
such operations are less costly than a full indexed-shuffle, which requires
a separate instruction cycle.

Predication "all zeros" needs to be "leave alone".  Detection of
ADD r1, rs1, rs0 cases result in nop on predication index 0, whereas
ADD r0, rs1, rs2 is actually a desirable copy from r2 into r0.
Destruction of destination indices requires a copy of the entire vector
in advance to avoid.

# References

* SIMD considered harmful <https://www.sigarch.org/simd-instructions-considered-harmful/>
* Link to first proposal <https://groups.google.com/a/groups.riscv.org/forum/#!topic/isa-dev/GuukrSjgBH8>
* Recommendation by Jacob Bachmeyer to make zero-overhead loop an
  "implicit program-counter" <https://groups.google.com/a/groups.riscv.org/d/msg/isa-dev/vYVi95gF2Mo/SHz6a4_lAgAJ>
* Re-continuing P-Extension proposal <https://groups.google.com/a/groups.riscv.org/forum/#!msg/isa-dev/IkLkQn3HvXQ/SEMyC9IlAgAJ>
* First Draft P-SIMD (DSP) proposal <https://groups.google.com/a/groups.riscv.org/forum/#!topic/isa-dev/vYVi95gF2Mo>
* B-Extension discussion <https://groups.google.com/a/groups.riscv.org/forum/#!topic/isa-dev/zi_7B15kj6s>
* Broadcom VideoCore-IV <https://docs.broadcom.com/docs/12358545>
  Figure 2 P17 and Section 3 on P16.
* Hwacha <https://www2.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-262.html>
* Hwacha <https://www2.eecs.berkeley.edu/Pubs/TechRpts/2015/EECS-2015-263.html>
* Vector Workshop <http://riscv.org/wp-content/uploads/2015/06/riscv-vector-workshop-june2015.pdf>
* Predication <https://groups.google.com/a/groups.riscv.org/forum/#!topic/isa-dev/XoP4BfYSLXA>
* Branch Divergence <https://jbush001.github.io/2014/12/07/branch-divergence-in-parallel-kernels.html>
* Life of Triangles (3D) <https://jbush001.github.io/2016/02/27/life-of-triangle.html>
* Videocore-IV <https://github.com/hermanhermitage/videocoreiv/wiki/VideoCore-IV-3d-Graphics-Pipeline>
* Discussion proposing CSRs that change ISA definition
  <https://groups.google.com/a/groups.riscv.org/forum/#!topic/isa-dev/InzQ1wr_3Ak>
* Zero-overhead loops <https://pdfs.semanticscholar.org/dbaa/66985cc730d4b44d79f519e96ec9c43ab5b7.pdf>
* Multi-ported VLIW Register File Implementation <https://ce-publications.et.tudelft.nl/publications/1517_multiple_contexts_in_a_multiported_vliw_register_file_impl.pdf>
* Fast context save/restore proposal <https://groups.google.com/a/groups.riscv.org/d/msgid/isa-dev/57F823FA.6030701%40gmail.com>
* Register File Bank Cacheing <https://www.princeton.edu/~rblee/ELE572Papers/MultiBankRegFile_ISCA2000.pdf>
* Expired Patent on Vector Virtual Memory solutions
  <https://patentimages.storage.googleapis.com/fc/f6/e2/2cbee92fcd8743/US5895501.pdf>
* Discussion on RVV "re-entrant" capabilities allowing operations to be
  restarted if an exception occurs (VM page-table miss)
  <https://groups.google.com/a/groups.riscv.org/d/msg/isa-dev/IuNFitTw9fM/CCKBUlzsAAAJ>
* Dot Product Vector <https://people.eecs.berkeley.edu/~biancolin/papers/arith17.pdf>