Files
Raptor/src/PIM/Compiler/PimBatchEmission.cpp
T
NiccoloN 41de3cb150
Validate Operations / validate-operations (push) Has been cancelled
add memory coalescing pass
better reports
refactor for more code-reuse and patter usage
fixes
2026-05-12 18:17:00 +02:00

137 lines
5.9 KiB
C++

#include "mlir/IR/Builders.h"
#include "mlir/IR/BuiltinOps.h"
#include "mlir/IR/IRMapping.h"
#include "src/Accelerators/PIM/Common/PimCommon.hpp"
#include "src/Accelerators/PIM/Compiler/PimBatchEmission.hpp"
using namespace mlir;
namespace onnx_mlir {
namespace {
static SmallVector<int32_t> getBatchCoreIds(pim::PimCoreBatchOp coreBatchOp) {
auto coreIdsAttr = coreBatchOp->getAttrOfType<DenseI32ArrayAttr>(onnx_mlir::kCoreIdsAttrName);
assert(coreIdsAttr && "pim.core_batch requires coreIds array attribute");
return SmallVector<int32_t>(coreIdsAttr.asArrayRef().begin(), coreIdsAttr.asArrayRef().end());
}
static SmallVector<int32_t> getLaneChunkCoreIds(ArrayRef<int32_t> coreIds, size_t laneCount, unsigned lane) {
SmallVector<int32_t> laneCoreIds;
laneCoreIds.reserve(coreIds.size() / laneCount);
for (size_t chunkIndex = 0; chunkIndex < coreIds.size() / laneCount; ++chunkIndex)
laneCoreIds.push_back(coreIds[chunkIndex * laneCount + lane]);
return laneCoreIds;
}
static void scalarizeBatchOpsInCore(pim::PimCoreOp scalarCore, size_t laneCount, unsigned lane) {
IRRewriter rewriter(scalarCore.getContext());
SmallVector<Operation*> batchOps;
scalarCore.walk([&](Operation* op) {
if (isa<pim::PimSendBatchOp,
pim::PimSendTensorBatchOp,
pim::PimReceiveBatchOp,
pim::PimReceiveTensorBatchOp,
pim::PimMemCopyHostToDevBatchOp>(op)) {
batchOps.push_back(op);
}
});
for (Operation* op : batchOps) {
rewriter.setInsertionPoint(op);
if (auto sendBatchOp = dyn_cast<pim::PimSendBatchOp>(op)) {
pim::PimSendOp::create(rewriter,
sendBatchOp.getLoc(),
sendBatchOp.getInput(),
sendBatchOp.getSizeAttr(),
rewriter.getI32IntegerAttr(sendBatchOp.getTargetCoreIds()[lane]));
rewriter.eraseOp(op);
continue;
}
if (auto sendTensorBatchOp = dyn_cast<pim::PimSendTensorBatchOp>(op)) {
pim::PimSendTensorOp::create(
rewriter,
sendTensorBatchOp.getLoc(),
sendTensorBatchOp.getInput(),
rewriter.getDenseI32ArrayAttr(getLaneChunkCoreIds(sendTensorBatchOp.getTargetCoreIds(), laneCount, lane)));
rewriter.eraseOp(op);
continue;
}
if (auto receiveBatchOp = dyn_cast<pim::PimReceiveBatchOp>(op)) {
auto scalarReceive =
pim::PimReceiveOp::create(rewriter,
receiveBatchOp.getLoc(),
receiveBatchOp.getOutput().getType(),
receiveBatchOp.getOutputBuffer(),
receiveBatchOp.getSizeAttr(),
rewriter.getI32IntegerAttr(receiveBatchOp.getSourceCoreIds()[lane]));
rewriter.replaceOp(op, scalarReceive->getResults());
continue;
}
if (auto receiveTensorBatchOp = dyn_cast<pim::PimReceiveTensorBatchOp>(op)) {
auto scalarReceive = pim::PimReceiveTensorOp::create(
rewriter,
receiveTensorBatchOp.getLoc(),
receiveTensorBatchOp.getOutput().getType(),
receiveTensorBatchOp.getOutputBuffer(),
rewriter.getDenseI32ArrayAttr(getLaneChunkCoreIds(receiveTensorBatchOp.getSourceCoreIds(), laneCount, lane)));
rewriter.replaceOp(op, scalarReceive->getResults());
continue;
}
auto memcpBatchOp = cast<pim::PimMemCopyHostToDevBatchOp>(op);
auto scalarCopy = pim::PimMemCopyHostToDevOp::create(rewriter,
memcpBatchOp.getLoc(),
memcpBatchOp.getOutput().getType(),
memcpBatchOp.getDeviceTarget(),
memcpBatchOp.getHostSource(),
memcpBatchOp.getDeviceTargetOffsetAttr(),
memcpBatchOp.getHostSourceOffsetAttr(),
memcpBatchOp.getSizeAttr());
rewriter.replaceOp(op, scalarCopy->getResults());
}
}
} // namespace
LogicalResult withScalarCoreFromBatchLane(pim::PimCoreBatchOp coreBatchOp,
unsigned lane,
llvm::function_ref<LogicalResult(pim::PimCoreOp)> callback) {
OwningOpRef<ModuleOp> scratchModule = ModuleOp::create(coreBatchOp.getLoc());
OpBuilder builder(scratchModule->getContext());
builder.setInsertionPointToStart(scratchModule->getBody());
size_t laneCount = static_cast<size_t>(coreBatchOp.getLaneCount());
size_t weightsPerLane = coreBatchOp.getWeights().size() / laneCount;
SmallVector<Value> laneWeights;
laneWeights.reserve(weightsPerLane);
for (size_t weightIndex = 0; weightIndex < weightsPerLane; ++weightIndex)
laneWeights.push_back(coreBatchOp.getWeights()[lane * weightsPerLane + weightIndex]);
auto coreIds = getBatchCoreIds(coreBatchOp);
auto scalarCore = pim::PimCoreOp::create(
builder, coreBatchOp.getLoc(), ValueRange(laneWeights), builder.getI32IntegerAttr(coreIds[lane]));
Block* block = builder.createBlock(&scalarCore.getBody(), scalarCore.getBody().end());
IRMapping mapper;
if (coreBatchOp.getBody().front().getNumArguments() == 1)
mapper.map(coreBatchOp.getBody().front().getArgument(0), coreBatchOp.getInputs()[lane]);
builder.setInsertionPointToEnd(block);
for (Operation& op : coreBatchOp.getBody().front()) {
Operation* cloned = builder.clone(op, mapper);
for (auto [originalResult, clonedResult] : llvm::zip(op.getResults(), cloned->getResults()))
mapper.map(originalResult, clonedResult);
}
if (block->empty() || !isa<pim::PimHaltOp>(block->back()))
pim::PimHaltOp::create(builder, coreBatchOp.getLoc());
scalarizeBatchOpsInCore(scalarCore, laneCount, lane);
return callback(scalarCore);
}
} // namespace onnx_mlir