(no commit message)

diff --git a/openpower/sv/remap/appendix.mdwn b/openpower/sv/remap/appendix.mdwn
index 7e6945e85b31fb7f4f49a833e68560a0dff65a11..0ef9e0b3860156362f42c06f1c7b57d2d0efd1f9 100644 (file)
--- a/openpower/sv/remap/appendix.mdwn
+++ b/openpower/sv/remap/appendix.mdwn
@@ -78,27 +78,8 @@ pipeline overlaps.  Out-of-order / Superscalar micro-architectures with
 register-renaming will have an easier time dealing with this than
 DSP-style SIMD micro-architectures.
 
 register-renaming will have an easier time dealing with this than
 DSP-style SIMD micro-architectures.
 

-## REMAP FFT, DFT, NTT
-
-The algorithm from a later section of this Appendix shows how FFT REMAP works,
-and it may be executed as a standalone python3 program.
-The executable code is designed to illustrate how a hardware
-implementation may generate Indices which are completely
-independent of the Execution of element-level operations,
-even for something as complex as a Triple-loop Tukey-Cooley
-Schedule. A comprehensive demo and test suite may be found
-[here](https://git.libre-soc.org/?p=openpower-isa.git;a=blob;f=src/openpower/decoder/isa/test_caller_svp64_fft.py;hb=HEAD)
-including Complex Number FFT which deploys Vertical-First Mode
-on top of the REMAP Schedules.
-
-Other uses include more than DFT and NTT: as abstracted RISC-paradigm
-the Schedules are not
-restricted in any way or tied to any particular instructtion.
-If the programmer can find any algorithm
-which has identical triple nesting then the FFT Schedule may be
-used even there.

 
 

-# 4x4 Matrix to vec4 Multiply (4x4 by 1x4)
+### 4x4 Matrix to vec4 Multiply (4x4 by 1x4)

 
 The following settings will allow a 4x4 matrix (starting at f8), expressed
 as a sequence of 16 numbers first by row then by column, to be multiplied
 
 The following settings will allow a 4x4 matrix (starting at f8), expressed
 as a sequence of 16 numbers first by row then by column, to be multiplied


@@ -149,6 +130,26 @@ initialised (usually to zero) however obviously if used as part
 of some other computation, which is frequently the case, then
 clearly the zeroing is not needed.
 
 of some other computation, which is frequently the case, then
 clearly the zeroing is not needed.
 

+## REMAP FFT, DFT, NTT
+
+The algorithm from a later section of this Appendix shows how FFT REMAP works,
+and it may be executed as a standalone python3 program.
+The executable code is designed to illustrate how a hardware
+implementation may generate Indices which are completely
+independent of the Execution of element-level operations,
+even for something as complex as a Triple-loop Tukey-Cooley
+Schedule. A comprehensive demo and test suite may be found
+[here](https://git.libre-soc.org/?p=openpower-isa.git;a=blob;f=src/openpower/decoder/isa/test_caller_svp64_fft.py;hb=HEAD)
+including Complex Number FFT which deploys Vertical-First Mode
+on top of the REMAP Schedules.
+
+Other uses include more than DFT and NTT: as abstracted RISC-paradigm
+the Schedules are not
+restricted in any way or tied to any particular instructtion.
+If the programmer can find any algorithm
+which has identical triple nesting then the FFT Schedule may be
+used even there.
+

 [[!tag standards]]
 
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 [[!tag standards]]
 
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