9f422915c7
This PR re-lands https://github.com/llvm/llvm-project/pull/156830 This PR aims at fixing the nvdsl examples which got a bit out of sync not being tested in the CI. The fixed bugs were related to the following PRs: - move to nanobind #118583 - split gpu module initialization #135478 - gpu dialect python API change #163883
92 lines
3.6 KiB
Python
92 lines
3.6 KiB
Python
# RUN: env SUPPORT_LIB=%mlir_cuda_runtime \
|
|
# RUN: sh -c 'if [[ "%mlir_run_cuda_sm90_tests" == "1" ]]; \
|
|
# RUN: then %PYTHON %s | FileCheck %s; \
|
|
# RUN: else export MLIR_NVDSL_PRINT_IR=1; \
|
|
# RUN: %PYTHON %s | FileCheck %s --check-prefix=DUMPIR; fi'
|
|
|
|
|
|
# ===----------------------------------------------------------------------===//
|
|
# Chapter 1 : 2D Saxpy
|
|
# ===----------------------------------------------------------------------===//
|
|
#
|
|
# This program demonstrates 2D Saxpy:
|
|
# 1. Use GPU dialect to allocate and copy memory host to gpu and vice versa
|
|
# 2. Computes 2D SAXPY kernel using operator overloading
|
|
# 3. Pass numpy arrays to MLIR as memref arguments
|
|
# 4. Verify MLIR program with reference computation in python
|
|
#
|
|
# ===----------------------------------------------------------------------===//
|
|
|
|
|
|
from mlir import ir
|
|
from mlir.dialects import gpu, memref
|
|
from tools.nvdsl import *
|
|
import numpy as np
|
|
|
|
|
|
@NVDSL.mlir_func
|
|
def saxpy(x, y, alpha):
|
|
# 1. Use MLIR GPU dialect to allocate and copy memory
|
|
token_ty = gpu.AsyncTokenType.get()
|
|
t1 = gpu.wait([])
|
|
x_dev, t2 = gpu.alloc(x.type, token_ty, [t1], [], [])
|
|
y_dev, t3 = gpu.alloc(y.type, token_ty, [t2], [], [])
|
|
t4 = gpu.memcpy(token_ty, [t3], x_dev, x)
|
|
t5 = gpu.memcpy(token_ty, [t4], y_dev, y)
|
|
t6 = gpu.wait([t5])
|
|
|
|
# 2. Compute 2D SAXPY kernel
|
|
@NVDSL.mlir_gpu_launch(grid=(M, 1, 1), block=(N, 1, 1))
|
|
def saxpy_kernel():
|
|
bidx = gpu.block_id(gpu.Dimension.x)
|
|
tidx = gpu.thread_id(gpu.Dimension.x)
|
|
x_val = memref.load(x_dev, [bidx, tidx])
|
|
y_val = memref.load(y_dev, [bidx, tidx])
|
|
|
|
# SAXPY: y[i] += a * x[i];
|
|
y_val += x_val * alpha
|
|
|
|
memref.store(y_val, y_dev, [bidx, tidx])
|
|
|
|
saxpy_kernel()
|
|
|
|
t7 = gpu.memcpy(token_ty, [t6], y, y_dev)
|
|
gpu.wait([t7])
|
|
|
|
|
|
# 3. Pass numpy arrays to MLIR
|
|
M = 256
|
|
N = 32
|
|
alpha = 2.0
|
|
x = np.random.randn(M, N).astype(np.float32)
|
|
y = np.ones((M, N), np.float32)
|
|
|
|
saxpy(x, y, alpha)
|
|
|
|
if os.getenv("MLIR_NVDSL_PRINT_IR") != "1":
|
|
# 4. Verify MLIR with reference computation
|
|
ref = np.ones((M, N), np.float32)
|
|
ref += x * alpha
|
|
np.testing.assert_allclose(y, ref, rtol=5e-03, atol=1e-01)
|
|
print("PASS")
|
|
# CHECK-NOT: Mismatched elements
|
|
# CHECK: PASS
|
|
|
|
# DUMPIR: func.func @saxpy(%[[ARG0:.*]]: memref<256x32xf32>, %[[ARG1:.*]]: memref<256x32xf32>, %[[ARG2:.*]]: f32) attributes {llvm.emit_c_interface} {
|
|
# DUMPIR: %[[WAIT0:.*]] = gpu.wait async
|
|
# DUMPIR: %[[MEMREF:.*]], %[[ASYNC0:.*]] = gpu.alloc async [%[[WAIT0]]] () : memref<256x32xf32>
|
|
# DUMPIR: %[[MEMREF0:.*]], %[[ASYNC1:.*]] = gpu.alloc async [%[[ASYNC0]]] () : memref<256x32xf32>
|
|
# DUMPIR: %[[MEMCPY1:.*]] = gpu.memcpy async [%[[ASYNC1]]] %[[MEMREF]], %[[ARG0]] : memref<256x32xf32>, memref<256x32xf32>
|
|
# DUMPIR: %[[MEMCPY2:.*]] = gpu.memcpy async [%[[MEMCPY1]]] %[[MEMREF0]], %[[ARG1]] : memref<256x32xf32>, memref<256x32xf32>
|
|
# DUMPIR: %[[WAIT1:.*]] = gpu.wait async [%[[MEMCPY2]]]
|
|
# DUMPIR: %[[LD0:.*]] = memref.load %[[MEMREF]][%{{.*}}, %{{.*}}] : memref<256x32xf32>
|
|
# DUMPIR: %[[LD1:.*]] = memref.load %[[MEMREF0]][%{{.*}}, %{{.*}}] : memref<256x32xf32>
|
|
# DUMPIR: %[[MUL:.*]] = arith.mulf %[[LD0]], %[[ARG2]] : f32
|
|
# DUMPIR: %[[ADD:.*]] = arith.addf %[[LD1]], %[[MUL]] : f32
|
|
# DUMPIR: memref.store %[[ADD]], %[[MEMREF0]][%{{.*}}, %{{.*}}] : memref<256x32xf32>
|
|
# DUMPIR: gpu.terminator
|
|
# DUMPIR: %[[MEMCPY3:.*]] = gpu.memcpy async [%[[WAIT1]]] %[[ARG1]], %[[MEMREF0]] : memref<256x32xf32>, memref<256x32xf32>
|
|
# DUMPIR: %[[WAIT2:.*]] = gpu.wait async [%[[MEMCPY3]]]
|
|
# DUMPIR: return
|
|
# DUMPIR: }
|