# RFC ls009 SVP64 REMAP instructions **URLs**: * * * * **Severity**: Major **Status**: New **Date**: 26 Mar 2023 **Target**: v3.2B **Source**: v3.0B **Books and Section affected**: ``` Book I, new Zero-Overhead-Loop Chapter. Appendix E Power ISA sorted by opcode Appendix F Power ISA sorted by version Appendix G Power ISA sorted by Compliancy Subset Appendix H Power ISA sorted by mnemonic ``` **Summary** ``` svremap - Re-Mapping of Register Element Offsets svindex - General-purpose setting of SHAPEs to be re-mapped svshape - Hardware-level setting of SHAPEs for element re-mapping svshape2 - Hardware-level setting of SHAPEs for element re-mapping (v2) ``` **Submitter**: Luke Leighton (Libre-SOC) **Requester**: Libre-SOC **Impact on processor**: ``` Addition of four new "Zero-Overhead-Loop-Control" DSP-style Vector-style Management Instructions which provide advanced features such as Matrix FFT DCT Hardware-Assist Schedules and general-purpose Index reordering. ``` **Impact on software**: ``` Requires support for new instructions in assembler, debuggers, and related tools. ``` **Keywords**: ``` Cray Supercomputing, Vectorisation, Zero-Overhead-Loop-Control (ZOLC), Scalable Vectors, Multi-Issue Out-of-Order, Sequential Programming Model, Digital Signal Processing (DSP) ``` **Motivation** These REMAP Management instructions provide state-of-the-art advanced capabilities to dramatically decrease instruction count and power reduction whilst retaining unprecedented general-purpose capability and a standard Sequential Execution Model. **Notes and Observations**: 1. TODO **Changes** Add the following entries to: * the Appendices of Book I * Instructions of Book I as a new Section * TODO-Form of Book I Section 1.6.1.6 and 1.6.2 ---------------- \newpage{} # REMAP REMAP is an advanced form of Vector "Structure Packing" that provides hardware-level support for commonly-used *nested* loop patterns that would otherwise require full inline loop unrolling. For more general reordering an Indexed REMAP mode is available. REMAP allows the usual sequential vector loop `0..VL-1` to be "reshaped" (re-mapped) from a linear form to a 2D or 3D transposed form, or "offset" to permit arbitrary access to elements (when elwidth overrides are used), independently on each Vector src or dest register. Aside from Indexed REMAP this is entirely Hardware-accelerated reordering and consequently not costly in terms of register access. It will however place a burden on Multi-Issue systems but no more than if the equivalent Scalar instructions were explicitly loop-unrolled without SVP64, and some advanced implementations may even find the Deterministic nature of the Scheduling to be easier on resources. The initial primary motivation of REMAP was for Matrix Multiplication, reordering of sequential data in-place: in-place DCT and FFT were easily justified given the exceptionally high usage in Computer Science. Four SPRs are provided which may be applied to any GPR, FPR or CR Field so that for example a single FMAC may be used in a single hardware-controlled 100% Deterministic loop to perform 5x3 times 3x4 Matrix multiplication, generating 60 FMACs *without needing explicit assembler unrolling*. Additional uses include regular "Structure Packing" such as RGB pixel data extraction and reforming. REMAP, like all of SV, is abstracted out, meaning that unlike traditional Vector ISAs which would typically only have a limited set of instructions that can be structure-packed (LD/ST typically), REMAP may be applied to literally any instruction: CRs, Arithmetic, Logical, LD/ST, anything. Note that REMAP does not *directly* apply to sub-vector elements but only to the group: that is what swizzle is for. Swizzle *can* however be applied to the same instruction as REMAP. As explained in [[sv/mv.swizzle]] and the [[svp64/appendix]], Pack and Unpack EXTRA Mode bits can extend down into Sub-vector elements to perform vec2/vec3/vec4 sequential reordering, but even here, REMAP is not *individually* extended down to the actual sub-vector elements themselves. In its general form, REMAP is quite expensive to set up, and on some implementations may introduce latency, so should realistically be used only where it is worthwhile. Given that even with latency the fact that up to 127 operations can be requested to be issued (from a single instruction) it should be clear that REMAP should not be dismissed for *potential* latency alone. Commonly-used patterns such as Matrix Multiply, DCT and FFT have helper instruction options which make REMAP easier to use. There are four types of REMAP: * **Matrix**, also known as 2D and 3D reshaping, can perform in-place Matrix transpose and rotate. The Shapes are set up for an "Outer Product" Matrix Multiply. * **FFT/DCT**, with full triple-loop in-place support: limited to Power-2 RADIX * **Indexing**, for any general-purpose reordering, also includes limited 2D reshaping. * **Parallel Reduction**, for scheduling a sequence of operations in a Deterministic fashion, in a way that may be parallelised, to reduce a Vector down to a single value. Best implemented on top of a Multi-Issue Out-of-Order Micro-architecture, REMAP Schedules are 100% Deterministic **including Indexing** and are designed to be incorporated in between the Decode and Issue phases, directly into Register Hazard Management. Parallel Reduction is unusual in that it requires a full vector array of results (not a scalar) and uses the rest of the result Vector for the purposes of storing intermediary calculations. As these intermediary results are Deterministically computed they may be useful. Additionally, because the intermediate results are always written out it is possible to service Precise Interrupts without affecting latency (a common limitation of Vector ISAs implementing explicit Parallel Reduction instructions). ## Basic principle * normal vector element read/write of operands would be sequential (0 1 2 3 ....) * this is not appropriate for (e.g.) Matrix multiply which requires accessing elements in alternative sequences (0 3 6 1 4 7 ...) * normal Vector ISAs use either Indexed-MV or Indexed-LD/ST to "cope" with this. both are expensive (copy large vectors, spill through memory) and very few Packed SIMD ISAs cope with non-Power-2. * REMAP **redefines** the order of access according to set (Deterministic) "Schedules". * The Schedules are not at all restricted to power-of-two boundaries making it unnecessary to have for example specialised 3x4 transpose instructions of other Vector ISAs. Only the most commonly-used algorithms in computer science have REMAP support, due to the high cost in both the ISA and in hardware. For arbitrary remapping the `Indexed` REMAP may be used. ## Example Usage * `svshape` to set the type of reordering to be applied to an otherwise usual `0..VL-1` hardware for-loop * `svremap` to set which registers a given reordering is to apply to (RA, RT etc) * `sv.{instruction}` where any Vectorised register marked by `svremap` will have its ordering REMAPPED according to the schedule set by `svshape`. The following illustrative example multiplies a 3x4 and a 5x3 matrix to create a 5x4 result: ``` svshape 5, 4, 3, 0, 0 svremap 15, 1, 2, 3, 0, 0, 0, 0 sv.fmadds *0, *8, *16, *0 ``` * svshape sets up the four SVSHAPE SPRS for a Matrix Schedule * svremap activates four out of five registers RA RB RC RT RS (15) * svremap requests: - RA to use SVSHAPE1 - RB to use SVSHAPE2 - RC to use SVSHAPE3 - RT to use SVSHAPE0 - RS Remapping to not be activated * sv.fmadds has RT=0.v, RA=8.v, RB=16.v, RC=0.v * With REMAP being active each register's element index is *independently* transformed using the specified SHAPEs. Thus the Vector Loop is arranged such that the use of the multiply-and-accumulate instruction executes precisely the required Schedule to perform an in-place in-registers Matrix Multiply with no need to perform additional Transpose or register copy instructions. The example above may be executed as a unit test and demo, [here](https://git.libre-soc.org/?p=openpower-isa.git;a=blob;f=src/openpower/decoder/isa/test_caller_svp64_matrix.py;h=c15479db9a36055166b6b023c7495f9ca3637333;hb=a17a252e474d5d5bf34026c25a19682e3f2015c3#l94) ## REMAP types This section summarises the motivation for each REMAP Schedule and briefly goes over their characteristics and limitations. Further details on the Deterministic Precise-Interruptible algorithms used in these Schedules is found in the [[sv/remap/appendix]]. ### Matrix (1D/2D/3D shaping) Matrix Multiplication is a huge part of High-Performance Compute, and 3D. In many PackedSIMD as well as Scalable Vector ISAs, non-power-of-two Matrix sizes are a serious challenge. PackedSIMD ISAs, in order to cope with for example 3x4 Matrices, recommend rolling data-repetition and loop-unrolling. Aside from the cost of the load on the L1 I-Cache, the trick only works if one of the dimensions X or Y are power-two. Prime Numbers (5x7, 3x5) become deeply problematic to unroll. Even traditional Scalable Vector ISAs have issues with Matrices, often having to perform data Transpose by pushing out through Memory and back, or computing Transposition Indices (costly) then copying to another Vector (costly). Matrix REMAP was thus designed to solve these issues by providing Hardware Assisted "Schedules" that can view what would otherwise be limited to a strictly linear Vector as instead being 2D (even 3D) *in-place* reordered. With both Transposition and non-power-two being supported the issues faced by other ISAs are mitigated. Limitations of Matrix REMAP are that the Vector Length (VL) is currently restricted to 127: up to 127 FMAs (or other operation) may be performed in total. Also given that it is in-registers only at present some care has to be taken on regfile resource utilisation. However it is perfectly possible to utilise Matrix REMAP to perform the three inner-most "kernel" loops of the usual 6-level large Matrix Multiply, without the usual difficulties associated with SIMD. Also the `svshape` instruction only provides access to part of the Matrix REMAP capability. Rotation and mirroring need to be done by programming the SVSHAPE SPRs directly, which can take a lot more instructions. Future versions of SVP64 will include EXT1xx prefixed variants (`psvshape`) which provide more comprehensive capacity and mitigate the need to write direct to the SVSHAPE SPRs. ### FFT/DCT Triple Loop DCT and FFT are some of the most astonishingly used algorithms in Computer Science. Radar, Audio, Video, R.F. Baseband and dozens more. At least two DSPs, TMS320 and Hexagon, have VLIW instructions specially tailored to FFT. An in-depth analysis showed that it is possible to do in-place in-register DCT and FFT as long as twin-result "butterfly" instructions are provided. These can be found in the [[openpower/isa/svfparith]] page if performing IEEE754 FP transforms. *(For fixed-point transforms, equivalent 3-in 2-out integer operations would be required)*. These "butterfly" instructions avoid the need for a temporary register because the two array positions being overwritten will be "in-flight" in any In-Order or Out-of-Order micro-architecture. DCT and FFT Schedules are currently limited to RADIX2 sizes and do not accept predicate masks. Given that it is common to perform recursive convolutions combining smaller Power-2 DCT/FFT to create larger DCT/FFTs in practice the RADIX2 limit is not a problem. A Bluestein convolution to compute arbitrary length is demonstrated by [Project Nayuki](https://www.nayuki.io/res/free-small-fft-in-multiple-languages/fft.py) ### Indexed The purpose of Indexing is to provide a generalised version of Vector ISA "Permute" instructions, such as VSX `vperm`. The Indexing is abstracted out and may be applied to much more than an element move/copy, and is not limited for example to the number of bytes that can fit into a VSX register. Indexing may be applied to LD/ST (even on Indexed LD/ST instructions such as `sv.lbzx`), arithmetic operations, extsw: there is no artificial limit. The only major caveat is that the registers to be used as Indices must not be modified by any instruction after Indexed Mode is established, and neither must MAXVL be altered. Additionally, no register used as an Index may exceed MAXVL-1. Failure to observe these conditions results in `UNDEFINED` behaviour. These conditions allow a Read-After-Write (RAW) Hazard to be created on the entire range of Indices to be subsequently used, but a corresponding Write-After-Read Hazard by any instruction that modifies the Indices **does not have to be created**. Given the large number of registers involved in Indexing this is a huge resource saving and reduction in micro-architectural complexity. MAXVL is likewise included in the RAW Hazards because it is involved in calculating how many registers are to be considered Indices. With these Hazard Mitigations in place, high-performance implementations may read-cache the Indices at the point where a given `svindex` instruction is called (or SVSHAPE SPRs - and MAXVL - directly altered) by issuing background GPR register file reads whilst other instructions are being issued and executed. The original motivation for Indexed REMAP was to mitigate the need to add an expensive `mv.x` to the Scalar ISA, which was likely to be rejected as a stand-alone instruction. Usually a Vector ISA would add a non-conflicting variant (as in VSX `vperm`) but it is common to need to permute by source, with the risk of conflict, that has to be resolved, for example, in AVX-512 with `conflictd`. Indexed REMAP on the other hand **does not prevent conflicts** (overlapping destinations), which on a superficial analysis may be perceived to be a problem, until it is recalled that, firstly, Simple-V is designed specifically to require Program Order to be respected, and that Matrix, DCT and FFT all *already* critically depend on overlapping Reads/Writes: Matrix uses overlapping registers as accumulators. Thus the Register Hazard Management needed by Indexed REMAP *has* to be in place anyway. The cost compared to Matrix and other REMAPs (and Pack/Unpack) is clearly that of the additional reading of the GPRs to be used as Indices, plus the setup cost associated with creating those same Indices. If any Deterministic REMAP can cover the required task, clearly it is adviseable to use it instead. *Programmer's note: some algorithms may require skipping of Indices exceeding VL-1, not MAXVL-1. This may be achieved programmatically by performing an `sv.cmp *BF,*RA,RB` where RA is the same GPRs used in the Indexed REMAP, and RB contains the value of VL returned from `setvl`. The resultant CR Fields may then be used as Predicate Masks to exclude those operations with an Index exceeding VL-1.* ### Parallel Reduction Vector Reduce Mode issues a deterministic tree-reduction schedule to the underlying micro-architecture. Like Scalar reduction, the "Scalar Base" (Power ISA v3.0B) operation is leveraged, unmodified, to give the *appearance* and *effect* of Reduction. In Horizontal-First Mode, Vector-result reduction **requires** the destination to be a Vector, which will be used to store intermediary results. Given that the tree-reduction schedule is deterministic, Interrupts and exceptions can therefore also be precise. The final result will be in the first non-predicate-masked-out destination element, but due again to the deterministic schedule programmers may find uses for the intermediate results. When Rc=1 a corresponding Vector of co-resultant CRs is also created. No special action is taken: the result *and its CR Field* are stored "as usual" exactly as all other SVP64 Rc=1 operations. Note that the Schedule only makes sense on top of certain instructions: X-Form with a Register Profile of `RT,RA,RB` is fine because two sources and the destination are all the same type. Like Scalar Reduction, nothing is prohibited: the results of execution on an unsuitable instruction may simply not make sense. With care, even 3-input instructions (madd, fmadd, ternlogi) may be used, and whilst it is down to the Programmer to walk through the process the Programmer can be confident that the Parallel-Reduction is guaranteed 100% Deterministic. Critical to note regarding use of Parallel-Reduction REMAP is that, exactly as with all REMAP Modes, the `svshape` instruction *requests* a certain Vector Length (number of elements to reduce) and then sets VL and MAXVL at the number of **operations** needed to be carried out. Thus, equally as importantly, like Matrix REMAP the total number of operations is restricted to 127. Any Parallel-Reduction requiring more operations will need to be done manually in batches (hierarchical recursive Reduction). Also important to note is that the Deterministic Schedule is arranged so that some implementations *may* parallelise it (as long as doing so respects Program Order and Register Hazards). Performance (speed) of any given implementation is neither strictly defined or guaranteed. As with the Vulkan(tm) Specification, strict compliance is paramount whilst performance is at the discretion of Implementors. **Parallel-Reduction with Predication** To avoid breaking the strict RISC-paradigm, keeping the Issue-Schedule completely separate from the actual element-level (scalar) operations, Move operations are **not** included in the Schedule. This means that the Schedule leaves the final (scalar) result in the first-non-masked element of the Vector used. With the predicate mask being dynamic (but deterministic) this result could be anywhere. If that result is needed to be moved to a (single) scalar register then a follow-up `sv.mv/sm=predicate rt, *ra` instruction will be needed to get it, where the predicate is the exact same predicate used in the prior Parallel-Reduction instruction. * If there was only a single bit in the predicate then the result will not have moved or been altered from the source vector prior to the Reduction * If there was more than one bit the result will be in the first element with a predicate bit set. In either case the result is in the element with the first bit set in the predicate mask. Programmer's Note: For *some* hardware implementations the vector-to-scalar copy may be a slow operation, as may the Predicated Parallel Reduction itself. It may be better to perform a pre-copy of the values, compressing them (VREDUCE-style) into a contiguous block, which will guarantee that the result goes into the very first element of the destination vector, in which case clearly no follow-up vector-to-scalar MV operation is needed. **Usage conditions** The simplest usage is to perform an overwrite, specifying all three register operands the same. ``` svshape parallelreduce, 6 sv.add *8, *8, *8 ``` The Reduction Schedule will issue the Parallel Tree Reduction spanning registers 8 through 13, by adjusting the offsets to RT, RA and RB as necessary (see "Parallel Reduction algorithm" in a later section). A non-overwrite is possible as well but just as with the overwrite version, only those destination elements necessary for storing intermediary computations will be written to: the remaining elements will **not** be overwritten and will **not** be zero'd. ``` svshape parallelreduce, 6 sv.add *0, *8, *8 ``` However it is critical to note that if the source and destination are not the same then the trick of using a follow-up vector-scalar MV will not work. ### Sub-Vector Horizontal Reduction To achieve Sub-Vector Horizontal Reduction, Pack/Unpack should be enabled, which will turn the Schedule around such that issuing of the Scalar Defined Words is done with SUBVL looping as the inner loop not the outer loop. Rc=1 with Sub-Vectors (SUBVL=2,3,4) is `UNDEFINED` behaviour. ## Determining Register Hazards For high-performance (Multi-Issue, Out-of-Order) systems it is critical to be able to statically determine the extent of Vectors in order to allocate pre-emptive Hazard protection. The next task is to eliminate masked-out elements using predicate bits, freeing up the associated Hazards. For non-REMAP situations `VL` is sufficient to ascertain early Hazard coverage, and with SVSTATE being a high priority cached quantity at the same level of MSR and PC this is not a problem. The problems come when REMAP is enabled. Indexed REMAP must instead use `MAXVL` as the earliest (simplest) batch-level Hazard Reservation indicator (after taking element-width overriding on the Index source into consideration), but Matrix, FFT and Parallel Reduction must all use completely different schemes. The reason is that VL is used to step through the total number of *operations*, not the number of registers. The "Saving Grace" is that all of the REMAP Schedules are 100% Deterministic. Advance-notice Parallel computation and subsequent cacheing of all of these complex Deterministic REMAP Schedules is *strongly recommended*, thus allowing clear and precise multi-issue batched Hazard coverage to be deployed, *even for Indexed Mode*. This is only possible for Indexed due to the strict guidelines given to Programmers. In short, there exists solutions to the problem of Hazard Management, with varying degrees of refinement possible at correspondingly increasing levels of complexity in hardware. A reminder: when Rc=1 each result register (element) has an associated co-result CR Field (one per result element). Thus above when determining the Write-Hazards for result registers the corresponding Write-Hazards for the corresponding associated co-result CR Field must not be forgotten, *including* when Predication is used. ## REMAP area of SVSTATE SPR The following bits of the SVSTATE SPR are used for REMAP: |32.33|34.35|36.37|38.39|40.41| 42.46 | 62 | | -- | -- | -- | -- | -- | ----- | ------ | |mi0 |mi1 |mi2 |mo0 |mo1 | SVme | RMpst | mi0-2 and mo0-1 each select SVSHAPE0-3 to apply to a given register. mi0-2 apply to RA, RB, RC respectively, as input registers, and likewise mo0-1 apply to output registers (RT/FRT, RS/FRS) respectively. SVme is 5 bits (one for each of mi0-2/mo0-1) and indicates whether the SVSHAPE is actively applied or not. * bit 0 of SVme indicates if mi0 is applied to RA / FRA / BA / BFA * bit 1 of SVme indicates if mi1 is applied to RB / FRB / BB * bit 2 of SVme indicates if mi2 is applied to RC / FRC / BC * bit 3 of SVme indicates if mo0 is applied to RT / FRT / BT / BF * bit 4 of SVme indicates if mo1 is applied to Effective Address / FRS / RS (LD/ST-with-update has an implicit 2nd write register, RA) The "persistence" bit if set will result in all Active REMAPs being applied indefinitely. ---------------- \newpage{} # svremap instruction SVRM-Form: svremap SVme,mi0,mi1,mi2,mo0,mo2,pst |0 |6 |11 |13 |15 |17 |19 |21 | 22.25 |26..31 | | -- | -- | -- | -- | -- | -- | -- | -- | ---- | ----- | | PO | SVme |mi0 | mi1 | mi2 | mo0 | mo1 | pst | rsvd | XO | SVRM-Form * svremap SVme,mi0,mi1,mi2,mo0,mo1,pst Pseudo-code: ``` # registers RA RB RC RT EA/FRS SVSHAPE0-3 indices SVSTATE[32:33] <- mi0 SVSTATE[34:35] <- mi1 SVSTATE[36:37] <- mi2 SVSTATE[38:39] <- mo0 SVSTATE[40:41] <- mo1 # enable bit for RA RB RC RT EA/FRS SVSTATE[42:46] <- SVme # persistence bit (applies to more than one instruction) SVSTATE[62] <- pst ``` Special Registers Altered: ``` None ``` `svremap` determines the relationship between registers and SVSHAPE SPRs. The bitmask `SVme` determines which registers have a REMAP applied, and mi0-mo1 determine which shape is applied to an activated register. the `pst` bit if cleared indicated that the REMAP operation shall only apply to the immediately-following instruction. If set then REMAP remains permanently enabled until such time as it is explicitly disabled, either by `setvl` setting a new MAXVL, or with another `svremap` instruction. `svindex` and `svshape2` are also capable of setting or clearing persistence, as well as partially covering a subset of the capability of `svremap` to set register-to-SVSHAPE relationships. Programmer's Note: applying non-persistent `svremap` to an instruction that has no REMAP enabled or is a Scalar operation will obviously have no effect but the bits 32 to 46 will at least have been set in SVSTATE. This may prove useful when using `svindex` or `svshape2`. Hardware Architectural Note: when persistence is not set it is critically important to treat the `svremap` and the following SVP64 instruction as an indivisible fused operation. *No state* is stored in the SVSTATE SPR in order to allow continuation should an Interrupt occur between the two instructions. Thus, Interrupts must be prohibited from occurring or other workaround deployed. When persistence is set this issue is moot. It is critical to note that if persistence is clear `svremap` is the **only** way to activate REMAP on any given (following) instruction. If persistence is set however then **all** SVP64 instructions go through REMAP as long as `SVme` is non-zero. ------------- \newpage{} # SHAPE Remapping SPRs There are four "shape" SPRs, SHAPE0-3, 32-bits in each, which have the same format. Shape is 32-bits. When SHAPE is set entirely to zeros, remapping is disabled: the register's elements are a linear (1D) vector. |31.30|29..28 |27..24| 23..21 | 20..18 | 17..12 |11..6 |5..0 | Mode | |---- |------ |------| ------ | ------- | ------- |----- |----- | ----- | |0b00 |skip |offset| invxyz | permute | zdimsz |ydimsz|xdimsz|Matrix | |0b00 |elwidth|offset|sk1/invxy|0b110/0b111|SVGPR|ydimsz|xdimsz|Indexed| |0b01 |submode|offset| invxyz | submode2| zdimsz |mode |xdimsz|DCT/FFT| |0b10 |submode|offset| invxyz | rsvd | rsvd |rsvd |xdimsz|Preduce| |0b11 | | | | | | | |rsvd | mode sets different behaviours (straight matrix multiply, FFT, DCT). * **mode=0b00** sets straight Matrix Mode * **mode=0b00** with permute=0b110 or 0b111 sets Indexed Mode * **mode=0b01** sets "FFT/DCT" mode and activates submodes * **mode=0b10** sets "Parallel Reduction" Schedules. ## Parallel Reduction Mode Creates the Schedules for Parallel Tree Reduction. * **submode=0b00** selects the left operand index * **submode=0b01** selects the right operand index * When bit 0 of `invxyz` is set, the order of the indices in the inner for-loop are reversed. This has the side-effect of placing the final reduced result in the last-predicated element. It also has the indirect side-effect of swapping the source registers: Left-operand index numbers will always exceed Right-operand indices. When clear, the reduced result will be in the first-predicated element, and Left-operand indices will always be *less* than Right-operand ones. * When bit 1 of `invxyz` is set, the order of the outer loop step is inverted: stepping begins at the nearest power-of two to half of the vector length and reduces by half each time. When clear the step will begin at 2 and double on each inner loop. ## FFT/DCT mode submode2=0 is for FFT. For FFT submode the following schedules may be selected: * **submode=0b00** selects the ``j`` offset of the innermost for-loop of Tukey-Cooley * **submode=0b10** selects the ``j+halfsize`` offset of the innermost for-loop of Tukey-Cooley * **submode=0b11** selects the ``k`` of exptable (which coefficient) When submode2 is 1 or 2, for DCT inner butterfly submode the following schedules may be selected. When submode2 is 1, additional bit-reversing is also performed. * **submode=0b00** selects the ``j`` offset of the innermost for-loop, in-place * **submode=0b010** selects the ``j+halfsize`` offset of the innermost for-loop, in reverse-order, in-place * **submode=0b10** selects the ``ci`` count of the innermost for-loop, useful for calculating the cosine coefficient * **submode=0b11** selects the ``size`` offset of the outermost for-loop, useful for the cosine coefficient ``cos(ci + 0.5) * pi / size`` When submode2 is 3 or 4, for DCT outer butterfly submode the following schedules may be selected. When submode is 3, additional bit-reversing is also performed. * **submode=0b00** selects the ``j`` offset of the innermost for-loop, * **submode=0b01** selects the ``j+1`` offset of the innermost for-loop, `zdimsz` is used as an in-place "Stride", particularly useful for column-based in-place DCT/FFT. ## Matrix Mode In Matrix Mode, skip allows dimensions to be skipped from being included in the resultant output index. this allows sequences to be repeated: ```0 0 0 1 1 1 2 2 2 ...``` or in the case of skip=0b11 this results in modulo ```0 1 2 0 1 2 ...``` * **skip=0b00** indicates no dimensions to be skipped * **skip=0b01** sets "skip 1st dimension" * **skip=0b10** sets "skip 2nd dimension" * **skip=0b11** sets "skip 3rd dimension" invxyz will invert the start index of each of x, y or z. If invxyz[0] is zero then x-dimensional counting begins from 0 and increments, otherwise it begins from xdimsz-1 and iterates down to zero. Likewise for y and z. offset will have the effect of offsetting the result by ```offset``` elements: ``` for i in 0..VL-1: GPR(RT + remap(i) + SVSHAPE.offset) = .... ``` this appears redundant because the register RT could simply be changed by a compiler, until element width overrides are introduced. also bear in mind that unlike a static compiler SVSHAPE.offset may be set dynamically at runtime. xdimsz, ydimsz and zdimsz are offset by 1, such that a value of 0 indicates that the array dimensionality for that dimension is 1. any dimension not intended to be used must have its value set to 0 (dimensionality of 1). A value of xdimsz=2 would indicate that in the first dimension there are 3 elements in the array. For example, to create a 2D array X,Y of dimensionality X=3 and Y=2, set xdimsz=2, ydimsz=1 and zdimsz=0 The format of the array is therefore as follows: ``` array[xdimsz+1][ydimsz+1][zdimsz+1] ``` However whilst illustrative of the dimensionality, that does not take the "permute" setting into account. "permute" may be any one of six values (0-5, with values of 6 and 7 indicating "Indexed" Mode). The table below shows how the permutation dimensionality order works: | permute | order | array format | | ------- | ----- | ------------------------ | | 000 | 0,1,2 | (xdim+1)(ydim+1)(zdim+1) | | 001 | 0,2,1 | (xdim+1)(zdim+1)(ydim+1) | | 010 | 1,0,2 | (ydim+1)(xdim+1)(zdim+1) | | 011 | 1,2,0 | (ydim+1)(zdim+1)(xdim+1) | | 100 | 2,0,1 | (zdim+1)(xdim+1)(ydim+1) | | 101 | 2,1,0 | (zdim+1)(ydim+1)(xdim+1) | | 110 | 0,1 | Indexed (xdim+1)(ydim+1) | | 111 | 1,0 | Indexed (ydim+1)(xdim+1) | In other words, the "permute" option changes the order in which nested for-loops over the array would be done. See executable python reference code for further details. *Note: permute=0b110 and permute=0b111 enable Indexed REMAP Mode, described below* With all these options it is possible to support in-place transpose, in-place rotate, Matrix Multiply and Convolutions, without being limited to Power-of-Two dimension sizes. ## Indexed Mode Indexed Mode activates reading of the element indices from the GPR and includes optional limited 2D reordering. In its simplest form (without elwidth overrides or other modes): ``` def index_remap(i): return GPR((SVSHAPE.SVGPR<<1)+i) + SVSHAPE.offset for i in 0..VL-1: element_result = .... GPR(RT + indexed_remap(i)) = element_result ``` With element-width overrides included, and using the pseudocode from the SVP64 [[sv/svp64/appendix#elwidth]] elwidth section this becomes: ``` def index_remap(i): svreg = SVSHAPE.SVGPR << 1 srcwid = elwid_to_bitwidth(SVSHAPE.elwid) offs = SVSHAPE.offset return get_polymorphed_reg(svreg, srcwid, i) + offs for i in 0..VL-1: element_result = .... rt_idx = indexed_remap(i) set_polymorphed_reg(RT, destwid, rt_idx, element_result) ``` Matrix-style reordering still applies to the indices, except limited to up to 2 Dimensions (X,Y). Ordering is therefore limited to (X,Y) or (Y,X) for in-place Transposition. Only one dimension may optionally be skipped. Inversion of either X or Y or both is possible (2D mirroring). Pseudocode for Indexed Mode (including elwidth overrides) may be written in terms of Matrix Mode, specifically purposed to ensure that the 3rd dimension (Z) has no effect: ``` def index_remap(ISHAPE, i): MSHAPE.skip = 0b0 || ISHAPE.sk1 MSHAPE.invxyz = 0b0 || ISHAPE.invxy MSHAPE.xdimsz = ISHAPE.xdimsz MSHAPE.ydimsz = ISHAPE.ydimsz MSHAPE.zdimsz = 0 # disabled if ISHAPE.permute = 0b110 # 0,1 MSHAPE.permute = 0b000 # 0,1,2 if ISHAPE.permute = 0b111 # 1,0 MSHAPE.permute = 0b010 # 1,0,2 el_idx = remap_matrix(MSHAPE, i) svreg = ISHAPE.SVGPR << 1 srcwid = elwid_to_bitwidth(ISHAPE.elwid) offs = ISHAPE.offset return get_polymorphed_reg(svreg, srcwid, el_idx) + offs ``` The most important observation above is that the Matrix-style remapping occurs first and the Index lookup second. Thus it becomes possible to perform in-place Transpose of Indices which may have been costly to set up or costly to duplicate (waste register file space). ------------- \newpage{} # svshape instruction Form: SVM-Form SV "Matrix" Form (see [[isatables/fields.text]]) svshape SVxd,SVyd,SVzd,SVRM,vf | 0.5|6.10 |11.15 |16..20 | 21..24 | 25 | 26..31| name | | -- | -- | --- | ----- | ------ | -- | ------| -------- | |OPCD| SVxd | SVyd | SVzd | SVRM | vf | XO | svshape | ``` # for convenience, VL to be calculated and stored in SVSTATE vlen <- [0] * 7 mscale[0:5] <- 0b000001 # for scaling MAXVL itercount[0:6] <- [0] * 7 SVSTATE[0:31] <- [0] * 32 # only overwrite REMAP if "persistence" is zero if (SVSTATE[62] = 0b0) then SVSTATE[32:33] <- 0b00 SVSTATE[34:35] <- 0b00 SVSTATE[36:37] <- 0b00 SVSTATE[38:39] <- 0b00 SVSTATE[40:41] <- 0b00 SVSTATE[42:46] <- 0b00000 SVSTATE[62] <- 0b0 SVSTATE[63] <- 0b0 # clear out all SVSHAPEs SVSHAPE0[0:31] <- [0] * 32 SVSHAPE1[0:31] <- [0] * 32 SVSHAPE2[0:31] <- [0] * 32 SVSHAPE3[0:31] <- [0] * 32 # set schedule up for multiply if (SVrm = 0b0000) then # VL in Matrix Multiply is xd*yd*zd xd <- (0b00 || SVxd) + 1 yd <- (0b00 || SVyd) + 1 zd <- (0b00 || SVzd) + 1 n <- xd * yd * zd vlen[0:6] <- n[14:20] # set up template in SVSHAPE0, then copy to 1-3 SVSHAPE0[0:5] <- (0b0 || SVxd) # xdim SVSHAPE0[6:11] <- (0b0 || SVyd) # ydim SVSHAPE0[12:17] <- (0b0 || SVzd) # zdim SVSHAPE0[28:29] <- 0b11 # skip z # copy SVSHAPE1[0:31] <- SVSHAPE0[0:31] SVSHAPE2[0:31] <- SVSHAPE0[0:31] SVSHAPE3[0:31] <- SVSHAPE0[0:31] # set up FRA SVSHAPE1[18:20] <- 0b001 # permute x,z,y SVSHAPE1[28:29] <- 0b01 # skip z # FRC SVSHAPE2[18:20] <- 0b001 # permute x,z,y SVSHAPE2[28:29] <- 0b11 # skip y # set schedule up for FFT butterfly if (SVrm = 0b0001) then # calculate O(N log2 N) n <- [0] * 3 do while n < 5 if SVxd[4-n] = 0 then leave n <- n + 1 n <- ((0b0 || SVxd) + 1) * n vlen[0:6] <- n[1:7] # set up template in SVSHAPE0, then copy to 1-3 # for FRA and FRT SVSHAPE0[0:5] <- (0b0 || SVxd) # xdim SVSHAPE0[12:17] <- (0b0 || SVzd) # zdim - "striding" (2D FFT) mscale <- (0b0 || SVzd) + 1 SVSHAPE0[30:31] <- 0b01 # Butterfly mode # copy SVSHAPE1[0:31] <- SVSHAPE0[0:31] SVSHAPE2[0:31] <- SVSHAPE0[0:31] # set up FRB and FRS SVSHAPE1[28:29] <- 0b01 # j+halfstep schedule # FRC (coefficients) SVSHAPE2[28:29] <- 0b10 # k schedule # set schedule up for (i)DCT Inner butterfly # SVrm Mode 2 (Mode 6 for iDCT) is for pre-calculated coefficients, # SVrm Mode 4 (Mode 12 for iDCT) is for on-the-fly (Vertical-First Mode) if ((SVrm = 0b0010) | (SVrm = 0b0100) | (SVrm = 0b1010) | (SVrm = 0b1100)) then # calculate O(N log2 N) n <- [0] * 3 do while n < 5 if SVxd[4-n] = 0 then leave n <- n + 1 n <- ((0b0 || SVxd) + 1) * n vlen[0:6] <- n[1:7] # set up template in SVSHAPE0, then copy to 1-3 # set up FRB and FRS SVSHAPE0[0:5] <- (0b0 || SVxd) # xdim SVSHAPE0[12:17] <- (0b0 || SVzd) # zdim - "striding" (2D DCT) mscale <- (0b0 || SVzd) + 1 if (SVrm = 0b1011) then SVSHAPE0[30:31] <- 0b11 # iDCT mode SVSHAPE0[18:20] <- 0b011 # iDCT Outer Butterfly sub-mode SVSHAPE0[21:23] <- 0b101 # "inverse" on outer and inner loop else SVSHAPE0[30:31] <- 0b01 # DCT mode SVSHAPE0[18:20] <- 0b100 # DCT Outer Butterfly sub-mode SVSHAPE0[6:11] <- 0b000010 # DCT Butterfly mode # copy SVSHAPE1[0:31] <- SVSHAPE0[0:31] # j+halfstep schedule SVSHAPE2[0:31] <- SVSHAPE0[0:31] # costable coefficients # for FRA and FRT SVSHAPE1[28:29] <- 0b01 # j+halfstep schedule # reset costable "striding" to 1 SVSHAPE2[12:17] <- 0b000000 # set schedule up for DCT COS table generation if (SVrm = 0b0101) | (SVrm = 0b1101) then # calculate O(N log2 N) vlen[0:6] <- [0] * 7 itercount[0:6] <- (0b00 || SVxd) + 0b0000001 itercount[0:6] <- (0b0 || itercount[0:5]) n <- [0] * 3 do while n < 5 if SVxd[4-n] = 0 then leave n <- n + 1 vlen[0:6] <- vlen + itercount itercount[0:6] <- (0b0 || itercount[0:5]) # set up template in SVSHAPE0, then copy to 1-3 # set up FRB and FRS SVSHAPE0[0:5] <- (0b0 || SVxd) # xdim SVSHAPE0[12:17] <- (0b0 || SVzd) # zdim - "striding" (2D DCT) mscale <- (0b0 || SVzd) + 1 SVSHAPE0[30:31] <- 0b01 # DCT/FFT mode SVSHAPE0[6:11] <- 0b000100 # DCT Inner Butterfly COS-gen mode if (SVrm = 0b0101) then SVSHAPE0[21:23] <- 0b001 # "inverse" on outer loop for DCT # copy SVSHAPE1[0:31] <- SVSHAPE0[0:31] SVSHAPE2[0:31] <- SVSHAPE0[0:31] # for cos coefficient SVSHAPE1[28:29] <- 0b10 # ci schedule SVSHAPE2[28:29] <- 0b11 # size schedule # set schedule up for iDCT / DCT inverse of half-swapped ordering if (SVrm = 0b0110) | (SVrm = 0b1110) | (SVrm = 0b1111) then vlen[0:6] <- (0b00 || SVxd) + 0b0000001 # set up template in SVSHAPE0 SVSHAPE0[0:5] <- (0b0 || SVxd) # xdim SVSHAPE0[12:17] <- (0b0 || SVzd) # zdim - "striding" (2D DCT) mscale <- (0b0 || SVzd) + 1 if (SVrm = 0b1110) then SVSHAPE0[18:20] <- 0b001 # DCT opposite half-swap if (SVrm = 0b1111) then SVSHAPE0[30:31] <- 0b01 # FFT mode else SVSHAPE0[30:31] <- 0b11 # DCT mode SVSHAPE0[6:11] <- 0b000101 # DCT "half-swap" mode # set schedule up for parallel reduction if (SVrm = 0b0111) then # calculate the total number of operations (brute-force) vlen[0:6] <- [0] * 7 itercount[0:6] <- (0b00 || SVxd) + 0b0000001 step[0:6] <- 0b0000001 i[0:6] <- 0b0000000 do while step SVI-Form | 0.5|6.10 |11.15 |16.20 | 21..25 | 26..31| name | Form | | -- | -- | --- | ---- | ----------- | ------| -------- | ---- | |OPCD| SVG | rmm | SVd | ew/yx/mm/sk | XO | svindex | SVI-Form | * svindex SVG,rmm,SVd,ew,SVyx,mm,sk Pseudo-code: ``` # based on nearest MAXVL compute other dimension MVL <- SVSTATE[0:6] d <- [0] * 6 dim <- SVd+1 do while d*dim N`. There is no requirement to set VL equal to a multiple of N. * **Modulo 2D transposed**: `SVd=M,sk=0,yx=1`, sets `xdim=M,ydim=CEIL(MAXVL/M)`. Beyond these mappings it becomes necessary to write directly to the SVSTATE SPRs manually. ------------- \newpage{} # svshape2 (offset-priority) SVM2-Form | 0-5|6-9 |10|11-15 |16-20 | 21-24 | 25 | 26-31 | Form | | -- |----|--| --- | ----- | ------ | -- | ------| -------- | | PO |offs|yx| rmm | SVd | 100/mm | sk | XO | SVM2-Form | * svshape2 offs,yx,rmm,SVd,sk,mm Pseudo-code: ``` # based on nearest MAXVL compute other dimension MVL <- SVSTATE[0:6] d <- [0] * 6 dim <- SVd+1 do while d*dim