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TheRock/rocm-libraries/projects/hipblaslt/tensilelite/Tensile/Components/SumUnroll.py
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derek.holloway 7502bf64a4
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Flatten subprojects into a single base monorepo
2026-09-02 16:34:47 -07:00

325 lines
20 KiB
Python

################################################################################
#
# Copyright (C) 2022-2025 Advanced Micro Devices, Inc. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
#
################################################################################
from rocisa.code import RegSet, Module
from rocisa.container import EXEC, vgpr, sgpr, DSModifiers, ContinuousRegister
from rocisa.enum import HighBitSel, SelectBit
from rocisa.instruction import SBarrier, \
SMovB32, SSetMask, VAddF32, VAddU32, VCmpXEqU32, \
VDot2F32BF16, VDot2F32F16, VLShiftLeftB32, VMovB32, VCvtBF16toFP32, \
ECvtF16toF32, ECvtPkFP8toF32, ECvtPkBF8toF32
from rocisa.functions import vectorStaticDivide, vectorStaticRemainder, vectorStaticMultiply
from ..Component import SumUnroll
from ..AsmMemoryHelpers import dsStore
from ..Common import printExit, log2
class SumUnrollMfma(SumUnroll):
kernel = {"EnableMatrixInstruction": True}
"""
Sum unroll for reduction
Use the same pattern as mfma
"""
def __call__(self):
assert(0)
def initSumUnroll(self, writer, kernel):
imod = Module("initSumUnroll")
idx = 0
while idx < writer.states.bias.numVgprValu:
imod.add(VMovB32(dst=vgpr("ValuSum+%d"%idx), src=0, comment="reset 0"))
idx += 1
# Init sum unroll, create pack for dot if needed
# Unregister is in storeSumLDS
if kernel["ProblemType"]["DataType"].numRegisters() < 1:
if kernel["ProblemType"]["DataType"].isHalf():
writer.defineSgpr("SumUnrollConstOne", 1)
imod.add(RegSet("s", "sgprSumUnrollConstOne", writer.sgprs["SumUnrollConstOne"]))
imod.add(SMovB32(dst=sgpr("SumUnrollConstOne"), src=hex(0x3c003c00), comment="packed 1.0"))
elif kernel["ProblemType"]["DataType"].isBFloat16() and writer.states.asmCaps['v_dot2_f32_bf16']:
writer.defineSgpr("SumUnrollConstOne", 1)
imod.add(RegSet("s", "sgprSumUnrollConstOne", writer.sgprs["SumUnrollConstOne"]))
imod.add(SMovB32(dst=sgpr("SumUnrollConstOne"), src=hex(0x3F803F80), comment="packed 1.0"))
else:
assert "[initSumUnroll] Unsupported data type"
return imod
def loopSum(self, writer, kernel, tP, u, innerUnroll):
tc = tP["tensorChar"]
imod = Module("SumUnroll%s_I%s" % (tc, innerUnroll))
m = (u) % (writer.states.numVgprBuffer) # local to use for MACs
# calculate constant
numRegistersIn = kernel["ProblemType"]["MacDataType%s"%tc].numRegisters()
numMIInput = kernel["MIInputPerThread%s"%tc]
vgprPerInput = int(numMIInput * numRegistersIn)
if tc == "A":
waveTile = kernel["MIWaveTile"][0]
numIterPerCoalescedRead = writer.states.numIterPerCoalescedReadA
numReadsIterCoalesced = writer.states.numReadsIterCoalescedA
elif tc == "B":
waveTile = kernel["MIWaveTile"][1]
numIterPerCoalescedRead = writer.states.numIterPerCoalescedReadB
numReadsIterCoalesced = writer.states.numReadsIterCoalescedB
else:
printExit("Unsupported tc %s"%tc)
# here we remap index to where it read for wider local read
# ex. if we read 2 iteration at a time,
# original : _ds_load_b64 valuA_X0_I0
# read 2 iter: _ds_load_b128 valuA_X0_I0 (we read valuA_X0_I0 and valuA_X1_I0)
# instead of using valuA_X1_I0, we use valuA_X0_I0+2 as mfma input
vgprBuffer_new = (m//numIterPerCoalescedRead)*numIterPerCoalescedRead
vgprBuffer_new_offset = m%numIterPerCoalescedRead*kernel["InnerUnroll"]*vgprPerInput
if kernel["ProblemType"]["MacDataType%s"%tc].isBFloat16():
hiBitsMaskVgpr = writer.vgprPool.checkOut(1, tag="loopSum_hiBitsMaskVgpr")
imod.add(VMovB32(dst=vgpr(hiBitsMaskVgpr), src=hex(0xffff0000), comment="mask 0xffff0000 for pack two bfloat16 element to 32bit"))
for iui in range(0, innerUnroll):
iui_new = (iui//numReadsIterCoalesced)*numReadsIterCoalesced
iui_new_offset = iui%numReadsIterCoalesced*vgprPerInput
for idx in range(0, waveTile):
new = idx*vgprPerInput*numReadsIterCoalesced
# valuStr = "Valu%s_X%u_I%u+%u+%u+%u" % (tc, vgprBuffer_new, iui_new, new, vgprBuffer_new_offset, iui_new_offset)
valuStr = "Valu%s_X%u_I%u+%u+%u" % (tc, vgprBuffer_new, iui_new, new, vgprBuffer_new_offset)
valuSumStr = "ValuSum+%u"%idx
# If direct ot vgpr, use "G2LA+%u+%u+%u", currently not supported
if kernel["ProblemType"]["DataType"].isHalf():
# FP16 BiasSrcA,B
tmpVgpr = writer.vgprPool.checkOut(1, tag="loopSum_tmpVgpr")
# First version only supports mfma with K > 1
if vgprPerInput > 1 and (vgprPerInput % 2 == 0):
for inputIdx in range(0, vgprPerInput):
if writer.states.asmCaps['v_dot2_f32_f16']:
imod.add(VDot2F32F16(dst=vgpr(valuSumStr), src0=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), src1=sgpr("SumUnrollConstOne"), src2=vgpr(valuSumStr), comment="sum K"))
else:
imod.add(ECvtF16toF32(dst=vgpr(tmpVgpr), src=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), sel=HighBitSel.LOW))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(ECvtF16toF32(dst=vgpr(tmpVgpr), src=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), sel=HighBitSel.HIGH))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr), src1=vgpr(valuSumStr), comment="sum K"))
else:
printExit("Currently unsupported vgprPerInput %u"%vgprPerInput)
writer.vgprPool.checkIn(tmpVgpr)
elif kernel["ProblemType"]["DataType"].isSingle():
inputIdx = 0
while inputIdx < vgprPerInput:
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), src1=vgpr(valuSumStr), comment="sum K"))
inputIdx += 1
elif kernel["ProblemType"]["MacDataType%s"%tc].isBFloat16():
# BF16 BiasSrcA,B
tmpVgpr = writer.vgprPool.checkOutAligned(2,2, tag="loopSum_tmpVgpr2")
if vgprPerInput > 1 and (vgprPerInput % 2 == 0):
for inputIdx in range(0, vgprPerInput):
if writer.states.asmCaps['v_dot2_f32_bf16']:
imod.add(VDot2F32BF16(dst=vgpr(valuSumStr), src0=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), src1=sgpr("SumUnrollConstOne"), src2=vgpr(valuSumStr), comment="sum K"))
else:
imod.add(VCvtBF16toFP32(dst=vgpr(tmpVgpr), src=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), vgprMask=None, vi=0))
imod.add(VCvtBF16toFP32(dst=vgpr(tmpVgpr+1), src=vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx)), vgprMask=vgpr(hiBitsMaskVgpr), vi=1))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+1), src1=vgpr(valuSumStr), comment="sum K"))
else:
printExit("Currently unsupported vgprPerInput %u"%vgprPerInput)
writer.vgprPool.checkIn(tmpVgpr)
elif kernel["ProblemType"]["MacDataType%s"%tc].isAnyFloat8():
#FP8
tmpVgpr = writer.vgprPool.checkOutAligned(4,2, tag="loopSum_tmpVgpr3")
if vgprPerInput > 1 and (vgprPerInput % 2 == 0):
for inputIdx in range(0, vgprPerInput):
src = vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx))
imod.add(ECvtPkFP8toF32(dst=vgpr(tmpVgpr,2), src=src, sel=HighBitSel.LOW, comment="convert to FP32"))
imod.add(ECvtPkFP8toF32(dst=vgpr(tmpVgpr+2,2), src=src, sel=HighBitSel.HIGH, comment="convert to FP32"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+1), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+2), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+3), src1=vgpr(valuSumStr), comment="sum K"))
else:
printExit("Currently unsupported vgprPerInput %u"%vgprPerInput)
writer.vgprPool.checkIn(tmpVgpr)
elif kernel["ProblemType"]["MacDataType%s"%tc].isAnyBFloat8():
#BF8
tmpVgpr = writer.vgprPool.checkOutAligned(4,2, tag="loopSum_tmpVgpr4")
if vgprPerInput > 1 and (vgprPerInput % 2 == 0):
for inputIdx in range(0, vgprPerInput):
src = vgpr("%s+%s"%(valuStr, iui_new_offset + inputIdx))
imod.add(ECvtPkBF8toF32(dst=vgpr(tmpVgpr,2), src=src, sel=HighBitSel.LOW, comment="convert to FP32"))
imod.add(ECvtPkBF8toF32(dst=vgpr(tmpVgpr+2,2), src=src, sel=HighBitSel.HIGH, comment="convert to FP32"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+1), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+2), src1=vgpr(valuSumStr), comment="sum K"))
imod.add(VAddF32(dst=vgpr(valuSumStr), src0=vgpr(tmpVgpr+3), src1=vgpr(valuSumStr), comment="sum K"))
else:
printExit("Currently unsupported vgprPerInput %u"%vgprPerInput)
writer.vgprPool.checkIn(tmpVgpr)
else:
printExit("Currently unsupported data type")
if kernel["ProblemType"]["MacDataType%s"%tc].isBFloat16():
writer.vgprPool.checkIn(hiBitsMaskVgpr)
return imod
"""
Store sum to LDS
Use the same pattern as local read, except the leading dimension is the sum index instead of free indices
maxKId is calculated to find out the length of the sum index.
"""
def storeSumLDS(self, writer, kernel, tP):
imod = Module("StoreSumLDS")
# Unregister defined sgpr
if kernel["ProblemType"]["DataType"].numRegisters() < 1:
if kernel["ProblemType"]["DataType"].isHalf():
writer.undefineSgpr("SumUnrollConstOne")
# bias data type
diasBpe = int(kernel["ProblemType"]["ComputeDataType"].numBytes())
# get constant parameter
tile01 = tP["tile01Idx"]
waveWidth = writer.states.kernel["WavefrontSize"]
wReg = writer.vgprPool.checkOut(1,"wReg") # quotient
tReg = writer.vgprPool.checkOut(1,"tReg") # remainder
kReg = writer.vgprPool.checkOut(1,"kReg") # remainder
tmpVgpr = writer.vgprPool.checkOutAligned(2,2,"tmpVgpr")
tmpVgprRes = ContinuousRegister(tmpVgpr, 2)
ldsVgpr = writer.vgprPool.checkOut(1,"ldsVgpr")
ldsVgpr1 = writer.vgprPool.checkOut(1,"ldsVgpr1")
dummy = writer.vgprPool.checkOut(1,"dummy")
# parameter for get each type index
tile10 = 1 - tile01
# Must init LraTileProperties in LraTileAssignment
assert writer.states.lraTileProperties[tile01] and writer.states.lraTileProperties[tile10]
dividendForKId = writer.states.lraTileProperties[tile01].dividendForKId
num1DBlocks = writer.states.lraTileProperties[tile01].num1DBlocks
num1DBlocks1 = writer.states.lraTileProperties[tile10].num1DBlocks
num1DWaves = writer.states.lraTileProperties[tile01].num1DWaves
dividedForBlkId = writer.states.lraTileProperties[tile01].dividedForBlkId
dividedForBlkId1 = writer.states.lraTileProperties[tile10].dividedForBlkId
dividedForWaveId = writer.states.lraTileProperties[tile01].dividedForWaveId
vectorWidth = writer.states.lraTileProperties[tile01].vectorWidth
maxKId = writer.states.lraTileProperties[tile01].maxKId
strideTile = maxKId
strideBlock = kernel["MatrixInstM"] * strideTile
strideWave = kernel["MatrixInstM"] * num1DBlocks * strideTile * vectorWidth
with writer.allocTmpSgpr(1, tag="StoreSumLDS_tmpSgprInfo") as tmpSgprInfo:
# tile offset
imod.add(vectorStaticRemainder(dummy, kReg, "Serial", waveWidth, tmpVgprRes, tmpSgprInfo, \
"0. thread id in wave: wtid = tid %% wavelength(%u)" % waveWidth))
imod.add(vectorStaticRemainder(dummy, tReg, kReg, kernel["MatrixInstN"], tmpVgprRes, tmpSgprInfo, \
"1. N offset: nIdx = wtid %% MI_N(%u)" % kernel["MatrixInstN"]))
imod.add(vectorStaticMultiply(vgpr(tReg), vgpr(tReg), strideTile, tmpSgprInfo, \
"1. N offset: nOffset = nIdx * nStride(%u)" % strideTile))
# block offset
# Here we calculate the coordinate of the block offset, and remove the duplicated blocks.
# For example we have block = 2x2, source swap = False:
# 0 1
# 2 3
# For tile01 = 0 we should only use 0, 2. For tile01 = 1 we should only use 0, 1.
imod.add(vectorStaticDivide(wReg, kReg, dividedForBlkId1, tmpVgprRes, \
"2-1. block offset: bnIdx = wtid / dividedForBlkId1(%u)" % dividedForBlkId1))
imod.add(vectorStaticRemainder(dummy, wReg, wReg, num1DBlocks1, tmpVgprRes, tmpSgprInfo, \
"2-1. block offset: bnIdx = bnIdx %% num1DBlocks1(%u)" % num1DBlocks1))
imod.add(VCmpXEqU32(dst=EXEC(), src0=vgpr(wReg), src1=0, comment="2-1. True if ans = 0"))
imod.add(vectorStaticDivide(wReg, kReg, dividedForBlkId, tmpVgprRes, \
"2. block offset: bnIdx = wtid / dividedForBlkId(%u)" % dividedForBlkId))
imod.add(vectorStaticRemainder(dummy, wReg, wReg, num1DBlocks, tmpVgprRes, tmpSgprInfo, \
"2. block offset: bnIdx = bnIdx %% num1DBlocks(%u)" % num1DBlocks))
imod.add(vectorStaticMultiply(vgpr(wReg), vgpr(wReg), strideBlock, tmpSgprInfo, \
"2. block offset: bnOffset = bnIdx * strideBlock(%u)" % strideBlock))
imod.add(VAddU32(dst=vgpr(tReg), src0=vgpr(wReg), src1=vgpr(tReg), \
comment="3. add N and block offset: bnOffset = block and N offset"))
imod.add(vectorStaticMultiply(vgpr(tReg), vgpr(tReg), vectorWidth, tmpSgprInfo, \
"3. apply VectorWidth: bnOffset = bnOffset * vw(%u)" % vectorWidth))
# unroll offset
imod.add(vectorStaticDivide(kReg, kReg, dividendForKId, tmpVgprRes, \
"4. K offset: kIdx = wtid / (MIN(%u) * MIBB(%u))" % (kernel["MatrixInstN"], kernel["MatrixInstB"])))
imod.add(vectorStaticMultiply(vgpr(kReg), vgpr(kReg), 1, tmpSgprInfo, \
"4. K offset: lrKOffset = kIdx * mStride(1)"))
imod.add(VAddU32(dst=vgpr(tReg), src0=vgpr(kReg), src1=vgpr(tReg), \
comment="5. offset in wave: lrOffset = bnOffset + lrKOffset"))
# wave offset
if num1DWaves > 1:
# FIXME: Should be two cases tile01 == 0 and tile01 == 1
imod.add(vectorStaticDivide(wReg, "Serial", dividedForWaveId, tmpVgprRes, \
"6. wave offset in N dimen: wtid = tid / dividedForWaveId(%u)" % dividedForWaveId))
# Here we calculate the coordinate of the block offset, and remove the duplicated wave.
if tile01 == 0:
imod.add(vectorStaticDivide(dummy, wReg, num1DWaves, tmpVgprRes, \
"6-1.mask duplicated: wtid0 = wtid / num1DWaves(%u)" % num1DWaves))
else:
imod.add(vectorStaticDivide(dummy, "Serial", waveWidth, tmpVgprRes, \
"6-1. wave offset in N dimen (waveWidth): wtid_1 = tid / waveWidth(%u)" % waveWidth))
imod.add(vectorStaticRemainder(dummy, dummy, dummy, kernel["MIWaveGroup"][0], tmpVgprRes, tmpSgprInfo, \
"6-1. wave offset in M dimen (MIWaveGroup0): wtid0 = wtid_1 %% MIWaveGroup0(%u)" % kernel["MIWaveGroup"][0]))
imod.add(VCmpXEqU32(dst=EXEC(), src0=vgpr(dummy), src1=0, comment="6-1. True if ans = 0"))
imod.add(vectorStaticRemainder(dummy, wReg, wReg, num1DWaves, tmpVgprRes, tmpSgprInfo, \
"6. wave offset in M dimen: wtid0 = wtid %% num1DWaves(%u)" % num1DWaves))
imod.add(vectorStaticMultiply(vgpr(wReg), vgpr(wReg), strideWave, tmpSgprInfo, \
"6. wave offset in M dimen: wOffset = wtid0 * W0Stride(%u)" % strideWave))
imod.add(VAddU32(dst=vgpr(tReg), src0=vgpr(wReg), src1=vgpr(tReg), \
comment="7. final local read offset: flrOffset = lrOffset + WOffset"))
imod.add(VLShiftLeftB32(dst=vgpr(tReg), src=vgpr(tReg), shiftHex=hex(log2(diasBpe)), \
comment="offset = offset*bpe" ))
# release register
writer.vgprPool.checkIn(wReg)
writer.vgprPool.checkIn(kReg)
writer.vgprPool.checkIn(tmpVgpr)
writer.vgprPool.checkIn(ldsVgpr)
writer.vgprPool.checkIn(ldsVgpr1)
writer.vgprPool.checkIn(dummy)
# Add barrier here to avoid race condition if lds offset starts from 0
if kernel["LdsOffsetBias"] == 0: # Compatible for both GSU1 and GSUM
imod.add(SBarrier(comment="Wait for all wavefronts"))
MIWaveGroupShape = [ kernel["MatrixInstM"] * kernel["MatrixInstBM"] * kernel["MIWaveGroup"][0] * kernel["VectorWidthA"], \
kernel["MatrixInstN"] * kernel["MatrixInstBN"] * kernel["MIWaveGroup"][1] * kernel["VectorWidthB"]]
numReadPerTileVector = vectorWidth
numVectorsPerTile = kernel["MIWaveTile"][tile01] // numReadPerTileVector
idx = 0
for vIdx in range(0, numVectorsPerTile):
for eIdx in range(0, numReadPerTileVector):
# normal case
offset_val = int((eIdx + vIdx * MIWaveGroupShape[tile01]) * maxKId * kernel["ProblemType"]["ComputeDataType"].numBytes())
bps = int(kernel["ProblemType"]["ComputeDataType"].numBytes())
ds = DSModifiers(offset=offset_val)
dst = vgpr(tReg)
vgprStr = "ValuSum+%u"%idx
numRegs = max(1, bps // 4)
imod.add(dsStore(bps, dstAddr=dst, src=vgpr(vgprStr, numRegs), ds=ds, comment="local store bias"))
idx += 1
# tReg
writer.vgprPool.checkIn(tReg)
imod.add(SSetMask(dst=EXEC(), src=-1, comment="reset mask" ))
# For later write in Global Write Batch
return imod