Skip to content

[MLIR][XeGPU] Add sg_map for scatter verification #124300

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Jan 30, 2025
Merged

[MLIR][XeGPU] Add sg_map for scatter verification #124300

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
7 changes: 2 additions & 5 deletions mlir/include/mlir/Dialect/XeGPU/IR/XeGPUOps.td
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -548,9 +548,7 @@ def XeGPU_PrefetchOp : XeGPU_Op<"prefetch", []> {
let hasVerifier = 1;
}

def XeGPU_LoadGatherOp : XeGPU_Op<"load", [AllRanksMatch<["value", "TensorDesc"]>,
AllElementTypesMatch<["value", "TensorDesc"]>,
AllElementCountsMatch<["value", "TensorDesc"]>]> {
def XeGPU_LoadGatherOp : XeGPU_Op<"load", [AllElementTypesMatch<["value", "TensorDesc"]>]> {
let summary = "load a set of scattered data points from memory.";

let description = [{ It (aka. load) load data per each work-item. The output
Expand Down Expand Up @@ -620,8 +618,7 @@ def XeGPU_LoadGatherOp : XeGPU_Op<"load", [AllRanksMatch<["value", "TensorDesc"]
let hasVerifier = 1;
}

def XeGPU_StoreScatterOp : XeGPU_Op<"store", [AllElementCountsMatch<["value", "TensorDesc"]>,
AllElementTypesMatch<["value", "TensorDesc"]>]> {
def XeGPU_StoreScatterOp : XeGPU_Op<"store", [AllElementTypesMatch<["value", "TensorDesc"]>]> {
let summary = "store data to scattered memory locations.";
let description = [{ It (aka. store) stores data to scattered memory locations. The value is
typically a 1D vector. But when the chunk size of the TensorDesc is larger than 1, it will be
Expand Down
47 changes: 44 additions & 3 deletions mlir/lib/Dialect/XeGPU/IR/XeGPUOps.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -453,7 +453,22 @@ LogicalResult CreateDescOp::verify() {
if (shape != tdescShape)
return emitOpError("Incorrect TensorDesc shape. ")
<< "Expected is " << makeString(shape) << "\n";

if (auto sgMap = tdescTy.getSGMapAttr()) {
// A work-item's slice of the TensorDesc with shape [sg_size] or
// [sg_size, chunk_size] will be [1] or [1, chunks_size] respectively,
// the mapping should reflect that.
if (sgMap.getWiData()[0] > 1)
return emitOpError("TensorDesc's SG map only supports multiple elements "
"contiguous along rows.");
if (chunkSize != static_cast<int>(sgMap.getWiData()[1]))
return emitOpError(
"TensorDesc's chunkSize must match WI's data mapping.");
if (int rank = tdescTy.getRank();
(sgMap.getWiLayout()[2 - rank] != tdescShape[0]))
return emitOpError("Detected a conflict between SG map's work-item "
"layout and TensorDesc shape. Check the index of "
"`subgroup_size` in WI layout map.");
}
return success();
}

Expand Down Expand Up @@ -512,10 +527,23 @@ LogicalResult LoadGatherOp::verify() {

if (tdescTy.getRank() == 2) {
if (!getTransposeAttr())
return emitOpError("load_gather has to be transposed.");
return emitOpError("load of rank-2 tensor has to be transposed.");
transpose({1, 0}, tdescShape);
}

if (auto sgMap = tdescTy.getSGMapAttr()) {
auto valueVecTy = cast<VectorType>(valueTy);
const int32_t wiData =
sgMap.getWiData()[0] > 1 ? sgMap.getWiData()[0] : sgMap.getWiData()[1];
// All represent the same concept: a number of row elements to store.
if (valueVecTy.getNumElements() != wiData ||
valueVecTy.getNumElements() != tdescTy.getChunkSize()) {
return emitOpError("Chunk size, vector size and wi_data must match.");
}
// Work-item's slice (i.e., vector shape to load) is [1] or [1, chunk_size].
tdescShape[tdescTy.getRank() - 1] = 1;
}

if (valueShape != tdescShape)
return emitOpError("Unexpected result shape")
<< "(Expected shape: " << makeString(tdescShape)
Expand Down Expand Up @@ -551,10 +579,23 @@ LogicalResult StoreScatterOp::verify() {

if (tdescTy.getRank() == 2) {
if (!getTransposeAttr())
return emitOpError("load_gather has to be transposed.");
return emitOpError("Store of a rank-2 tensor has to be transposed.");
transpose({1, 0}, tdescShape);
}

if (auto sgMap = tdescTy.getSGMapAttr()) {
auto valueVecTy = cast<VectorType>(valueTy);
const int32_t wiData =
sgMap.getWiData()[0] > 1 ? sgMap.getWiData()[0] : sgMap.getWiData()[1];
// All represent the same concept: a number of row elements to store.
if (valueVecTy.getNumElements() != wiData ||
valueVecTy.getNumElements() != tdescTy.getChunkSize()) {
return emitOpError("Chunk size, vector size and wi_data must match.");
}
// Work-item's slice (i.e., vector to store) is [1] or [1, chunk_size].
tdescShape[tdescTy.getRank() - 1] = 1;
}

if (valueShape != tdescShape)
return emitOpError("Unexpected value shape")
<< "(Expected shape: " << makeString(tdescShape)
Expand Down
62 changes: 60 additions & 2 deletions mlir/test/Dialect/XeGPU/XeGPUOps.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -163,11 +163,69 @@ gpu.func @test_create_tdesc_vc_1(%src: memref<?xf32, 3>) {
gpu.func @test_create_tdesc_vc_with_sg_map(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
//CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 1]>>
%1 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 1]>>
//CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
%1 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
gpu.return
}

// CHECK: gpu.func @test_load_with_sg_map(%[[arg0:.*]]: ui64) {
gpu.func @test_load_with_sg_map(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
//CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
%1 = arith.constant dense<1>: vector<4xi1>
//CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
%2 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
//CHECK: %[[R1:.*]] = xegpu.load %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<2x1xf32>
%3 = xegpu.load %2, %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<2x1xf32>
gpu.return
}

// CHECK: gpu.func @test_load_with_sg_map_2(%[[arg0:.*]]: ui64) {
gpu.func @test_load_with_sg_map_2(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
//CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
%1 = arith.constant dense<1>: vector<4xi1>
//CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
%2 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
//CHECK: %[[R1:.*]] = xegpu.load %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}> : !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1> -> vector<1xf32>
%3 = xegpu.load %2, %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}> : !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1> -> vector<1xf32>
gpu.return
}

// CHECK: gpu.func @test_store_with_sg_map(%[[arg0:.*]]: ui64) {
gpu.func @test_store_with_sg_map(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
//CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
%1 = arith.constant dense<1>: vector<4xi1>
//CHECK: %[[cst2:.*]] = arith.constant dense<2.900000e+00> : vector<2x1xf32>
%2 = arith.constant dense<2.9>: vector<2x1xf32>
//CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
%3 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
//CHECK: xegpu.store %[[cst2]], %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : vector<2x1xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2 : i64>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
xegpu.store %2, %3, %1 <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>, transpose}> : vector<2x1xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
gpu.return
}

// CHECK: gpu.func @test_store_with_sg_map_2(%[[arg0:.*]]: ui64) {
gpu.func @test_store_with_sg_map_2(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%0 = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
//CHECK: %[[cst1:.*]] = arith.constant dense<true> : vector<4xi1>
%1 = arith.constant dense<1>: vector<4xi1>
//CHECK: %[[cst2:.*]] = arith.constant dense<2.900000e+00> : vector<1xf32>
%2 = arith.constant dense<2.9>: vector<1xf32>
//CHECK: %[[R0:.*]] = xegpu.create_tdesc %[[arg0]], %[[cst]] : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
%3 = xegpu.create_tdesc %src, %0 : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>
//CHECK: xegpu.store %[[cst2]], %[[R0]], %[[cst1]] <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>}> : vector<1xf32>, !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1>
xegpu.store %2, %3, %1 <{l1_hint = #xegpu.cache_hint<write_back>, l2_hint = #xegpu.cache_hint<uncached>}> : vector<1xf32>, !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [1, 1]>>, vector<4xi1>
gpu.return
}



// CHECK: gpu.func @test_prefetch_vc(%[[arg0:.*]]: ui64) {
gpu.func @test_prefetch_vc(%src: ui64) {
//CHECK: %[[cst:.*]] = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
Expand Down
77 changes: 77 additions & 0 deletions mlir/test/Dialect/XeGPU/invalid.mlir
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -170,6 +170,83 @@ func.func @test_prefetch_vc_2(%src: ui64) {
return
}

// -----
func.func @test_create_tdesc_sg_map_1(%src: ui64) {
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
// expected-error@+1 {{Detected a conflict between SG map's work-item layout and TensorDesc shape. Check the index of `subgroup_size` in WI layout map}}
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4xf32, #xegpu.scatter_tdesc_attr<>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 1]>>
return
}

// -----
func.func @test_create_tdesc_sg_map_2(%src: ui64) {
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
// expected-error@+1 {{TensorDesc's SG map only supports multiple elements contiguous along rows}}
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [1, 4], wi_data = [2, 1]>>
return
}

// -----
func.func @test_create_tdesc_sg_map_3(%src: ui64) {
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
// expected-error@+1 {{TensorDesc's chunkSize must match WI's data mapping}}
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x3xf32, #xegpu.scatter_tdesc_attr<chunk_size = 3>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
return
}

// -----
func.func @test_load_gather_sg_map_1(%src: ui64) {
%0 = arith.constant dense<1>: vector<4xi1>
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
// expected-error@+1 {{Unexpected result shape(Expected shape: [2, 1], Given shape: [1, 2])}}
%2 = xegpu.load %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<1x2xf32>
return
}

// -----
func.func @test_load_gather_sg_map_2(%src: ui64) {
%0 = arith.constant dense<1>: vector<4xi1>
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
// expected-error@+1 {{Unexpected result shape(Expected shape: [2, 1], Given shape: [2])}}
%2 = xegpu.load %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<2xf32>
return
}

// -----
func.func @test_load_gather_sg_map_3(%src: ui64) {
%0 = arith.constant dense<1>: vector<4xi1>
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
// expected-error@+1 {{Chunk size, vector size and wi_data must match}}
%2 = xegpu.load %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1> -> vector<1xf32>
return
}


// -----
func.func @test_store_scatter_sg_map_1(%src: ui64) {
%0 = arith.constant dense<1>: vector<4xi1>
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%val = arith.constant dense<2.9>: vector<1x2xf32>
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
// expected-error@+1 {{Unexpected value shape(Expected shape: [2, 1], Given shape: [1, 2])}}
xegpu.store %val, %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : vector<1x2xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
return
}

// -----
func.func @test_store_scatter_sg_map_2(%src: ui64) {
%0 = arith.constant dense<1>: vector<4xi1>
%cst = arith.constant dense<[0, 8, 16, 24]> : vector<4xindex>
%val = arith.constant dense<2.9>: vector<2xf32>
%1 = xegpu.create_tdesc %src, %cst : ui64, vector<4xindex> -> !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>
// expected-error@+1 {{Unexpected value shape(Expected shape: [2, 1], Given shape: [2])}}
xegpu.store %val, %1, %0 <{l1_hint = #xegpu.cache_hint<cached>, transpose}> : vector<2xf32>, !xegpu.tensor_desc<4x2xf32, #xegpu.scatter_tdesc_attr<chunk_size = 2>, #xegpu.sg_map<wi_layout = [4, 1], wi_data = [1, 2]>>, vector<4xi1>
return
}

// -----
func.func @test_load_gather_vc_1(%src: memref<24x32xf16>) {
%0 = arith.constant dense<1>: vector<4xi1>
Expand Down