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未验证 提交 34f1628c 编写于 作者: Q Qi Li 提交者： GitHub
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[ROCM] update fluid platform for rocm39 (part2), test=develop (#30774)

上级 5ded39f2
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paddle/fluid/platform/float16.h
浏览文件 @ 34f1628c
......@@ -90,7 +90,7 @@ struct PADDLE_ALIGN(2) float16 {
// Constructors
#ifdef PADDLE_CUDA_FP16
HOSTDEVICE inline explicit float16(const half& h) {
#if (defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP))
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#if defined(PADDLE_WITH_HIP) || CUDA_VERSION >= 9000
x = reinterpret_cast<__half_raw*>(const_cast<half*>(&h))->x;
#else
......@@ -366,10 +366,11 @@ struct PADDLE_ALIGN(2) float16 {
// CUDA 7.5 and 8.0 do not. The arithmetic operators defined here are
// for users to write similar CUDA code in CUDA 7.5 and 8.0 as in
// CUDA 9.0 regarding the half data type.
// xuan[TODO] change for rocm
#if defined(PADDLE_CUDA_FP16) && CUDA_VERSION < 9000
// ROCM has built-in arithmetic operators as not defined
// __HIP_NO_HALF_OPERATORS__
#if defined(PADDLE_CUDA_FP16) && !defined(__HIPCC__) && CUDA_VERSION < 9000
DEVICE inline half operator+(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hadd(a, b);
#else
float res = static_cast<float>(float16(a)) + static_cast<float>(float16(b));
......@@ -378,7 +379,7 @@ DEVICE inline half operator+(const half& a, const half& b) {
}
DEVICE inline half operator-(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hsub(a, b);
#else
float res = static_cast<float>(float16(a)) - static_cast<float>(float16(b));
......@@ -387,7 +388,7 @@ DEVICE inline half operator-(const half& a, const half& b) {
}
DEVICE inline half operator*(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hmul(a, b);
#else
float res = static_cast<float>(float16(a)) * static_cast<float>(float16(b));
......@@ -396,7 +397,7 @@ DEVICE inline half operator*(const half& a, const half& b) {
}
DEVICE inline half operator/(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
float num = __half2float(a);
float denom = __half2float(b);
return __float2half(num / denom);
......@@ -407,7 +408,7 @@ DEVICE inline half operator/(const half& a, const half& b) {
}
DEVICE inline half operator-(const half& a) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hneg(a);
#else
float res = -static_cast<float>(float16(a));
......@@ -438,7 +439,7 @@ DEVICE inline half& operator/=(half& a, const half& b) { // NOLINT
#endif
DEVICE inline bool operator==(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __heq(a, b);
#else
return static_cast<float>(float16(a)) == static_cast<float>(float16(b));
......@@ -446,7 +447,7 @@ DEVICE inline bool operator==(const half& a, const half& b) {
}
DEVICE inline bool operator!=(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hne(a, b);
#else
return static_cast<float>(float16(a)) != static_cast<float>(float16(b));
......@@ -454,7 +455,7 @@ DEVICE inline bool operator!=(const half& a, const half& b) {
}
DEVICE inline bool operator<(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hlt(a, b);
#else
return static_cast<float>(float16(a)) < static_cast<float>(float16(b));
......@@ -462,7 +463,7 @@ DEVICE inline bool operator<(const half& a, const half& b) {
}
DEVICE inline bool operator<=(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hle(a, b);
#else
return static_cast<float>(float16(a)) <= static_cast<float>(float16(b));
......@@ -470,7 +471,7 @@ DEVICE inline bool operator<=(const half& a, const half& b) {
}
DEVICE inline bool operator>(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hgt(a, b);
#else
return static_cast<float>(float16(a)) > static_cast<float>(float16(b));
......@@ -478,7 +479,7 @@ DEVICE inline bool operator>(const half& a, const half& b) {
}
DEVICE inline bool operator>=(const half& a, const half& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hge(a, b);
#else
return static_cast<float>(float16(a)) >= static_cast<float>(float16(b));
......@@ -489,9 +490,8 @@ DEVICE inline bool operator>=(const half& a, const half& b) {
// Arithmetic operators for float16 on GPU
#if defined(PADDLE_CUDA_FP16)
// HIPCC has compile error if call __device__ function __hadd in __host__
// __device__ function
// HIPCC has compile error if call __device__ function __hadd, __hsub, etc.
// in __host__ __device__ function
#if defined(__HIPCC__)
DEVICE inline float16 operator+(const float16& a, const float16& b) {
return float16(__hadd(half(a), half(b)));
......@@ -509,8 +509,6 @@ HOSTDEVICE inline float16 operator+(const float16& a, const float16& b) {
}
#endif
// HIPCC has compile error if call __device__ function __hsub in __host__
// __device__ function
#if defined(__HIPCC__)
DEVICE inline float16 operator-(const float16& a, const float16& b) {
return float16(__hsub(half(a), half(b)));
......@@ -528,8 +526,6 @@ HOSTDEVICE inline float16 operator-(const float16& a, const float16& b) {
}
#endif
// HIPCC has compile error if call __device__ function __hmul in __host__
// __device__ function
#if defined(__HIPCC__)
DEVICE inline float16 operator*(const float16& a, const float16& b) {
return float16(__hmul(half(a), half(b)));
......@@ -547,8 +543,16 @@ HOSTDEVICE inline float16 operator*(const float16& a, const float16& b) {
}
#endif
#if defined(__HIPCC__)
DEVICE inline float16 operator/(const float16& a, const float16& b) {
return float16(__hdiv(half(a), half(b)));
}
HOST inline float16 operator/(const float16& a, const float16& b) {
return float16(static_cast<float>(a) / static_cast<float>(b));
}
#else
HOSTDEVICE inline float16 operator/(const float16& a, const float16& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
// TODO(kexinzhao): check which cuda version starts to support __hdiv
float num = __half2float(half(a));
float denom = __half2float(half(b));
......@@ -557,9 +561,8 @@ HOSTDEVICE inline float16 operator/(const float16& a, const float16& b) {
return float16(static_cast<float>(a) / static_cast<float>(b));
#endif
}
#endif
// HIPCC has compile error if call __device__ function __hneg in __host__
// __device__ function
#if defined(__HIPCC__)
DEVICE inline float16 operator-(const float16& a) {
return float16(__hneg(half(a)));
......@@ -601,8 +604,8 @@ HOSTDEVICE inline float16& operator/=(float16& a, const float16& b) { // NOLINT
return a;
}
// HIPCC has compile error if call __device__ function __heq in __host__
// __device__ function
// HIPCC has compile error if call __device__ function __heq, __hne, etc.
// in __host__ __device__ function
#if defined(__HIPCC__)
DEVICE inline bool operator==(const float16& a, const float16& b) {
return __heq(half(a), half(b));
......@@ -610,7 +613,7 @@ DEVICE inline bool operator==(const float16& a, const float16& b) {
HOST inline bool operator==(const float16& a, const float16& b) {
return static_cast<float>(a) == static_cast<float>(b);
}
#else // CUDA
#else // __HIPCC__
HOSTDEVICE inline bool operator==(const float16& a, const float16& b) {
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __heq(half(a), half(b));
......@@ -618,47 +621,92 @@ HOSTDEVICE inline bool operator==(const float16& a, const float16& b) {
return static_cast<float>(a) == static_cast<float>(b);
#endif
}
#endif
#endif // __HIPCC__
#if defined(__HIPCC__)
DEVICE inline bool operator!=(const float16& a, const float16& b) {
return __hne(half(a), half(b));
}
HOST inline bool operator!=(const float16& a, const float16& b) {
return static_cast<float>(a) != static_cast<float>(b);
}
#else // __HIPCC__
HOSTDEVICE inline bool operator!=(const float16& a, const float16& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hne(half(a), half(b));
#else
return static_cast<float>(a) != static_cast<float>(b);
#endif
}
#endif // __HIPCC__
#if defined(__HIPCC__)
DEVICE inline bool operator<(const float16& a, const float16& b) {
return __hlt(half(a), half(b));
}
HOST inline bool operator<(const float16& a, const float16& b) {
return static_cast<float>(a) < static_cast<float>(b);
}
#else // __HIPCC__
HOSTDEVICE inline bool operator<(const float16& a, const float16& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hlt(half(a), half(b));
#else
return static_cast<float>(a) < static_cast<float>(b);
#endif
}
#endif // __HIPCC__
#if defined(__HIPCC__)
DEVICE inline bool operator<=(const float16& a, const float16& b) {
return __hle(half(a), half(b));
}
HOST inline bool operator<=(const float16& a, const float16& b) {
return static_cast<float>(a) <= static_cast<float>(b);
}
#else // __HIPCC__
HOSTDEVICE inline bool operator<=(const float16& a, const float16& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hle(half(a), half(b));
#else
return static_cast<float>(a) <= static_cast<float>(b);
#endif
}
#endif // __HIPCC__
#if defined(__HIPCC__)
DEVICE inline bool operator>(const float16& a, const float16& b) {
return __hgt(half(a), half(b));
}
HOST inline bool operator>(const float16& a, const float16& b) {
return static_cast<float>(a) > static_cast<float>(b);
}
#else // __HIPCC__
HOSTDEVICE inline bool operator>(const float16& a, const float16& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hgt(half(a), half(b));
#else
return static_cast<float>(a) > static_cast<float>(b);
#endif
}
#endif // __HIPCC__
#if defined(__HIPCC__)
DEVICE inline bool operator>=(const float16& a, const float16& b) {
return __hge(half(a), half(b));
}
HOST inline bool operator>=(const float16& a, const float16& b) {
return static_cast<float>(a) >= static_cast<float>(b);
}
#else // __HIPCC__
HOSTDEVICE inline bool operator>=(const float16& a, const float16& b) {
#if defined(__HIPCC__) || (defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530)
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ >= 530
return __hge(half(a), half(b));
#else
return static_cast<float>(a) >= static_cast<float>(b);
#endif
}
#endif // __HIPCC__
// Arithmetic operators for float16 on ARMv8.2-A CPU
#elif defined(PADDLE_WITH_NATIVE_FP16)
......
paddle/fluid/platform/float16_test.cu
浏览文件 @ 34f1628c
......@@ -22,30 +22,109 @@ limitations under the License. */
#include "paddle/fluid/platform/enforce.h"
#define ARITHMETIC_KERNEL(op_type, sign) \
__global__ void op_type(const half* in1, const half* in2, half* out) { \
__global__ void op_type(const half *in1, const half *in2, half *out) { \
out[0] = in1[0] sign in2[0]; \
}
#define COMPOUND_KERNEL(op_type, sign) \
__global__ void op_type(half* in1, const half* in2) { in1[0] sign in2[0]; }
__global__ void op_type(half *in1, const half *in2) { in1[0] sign in2[0]; }
#define COMPARISON_KERNEL(op_type, sign) \
__global__ void op_type(const half* in1, const half* in2, bool* out) { \
__global__ void op_type(const half *in1, const half *in2, bool *out) { \
out[0] = in1[0] sign in2[0]; \
}
#ifdef PADDLE_WITH_HIP
#define ARITHMETIC_KERNEL_LAUNCH(op_type) \
void Test##op_type(float v_in1, float v_in2, float v_out) { \
LOG(INFO) << "Test " << #op_type << " on GPU!"; \
half *in1, *in2, *out; \
half *d_in1, *d_in2, *d_out; \
int size = sizeof(half); \
cudaMalloc(reinterpret_cast<void**>(&d_in1), size); \
cudaMalloc(reinterpret_cast<void**>(&d_in2), size); \
cudaMalloc(reinterpret_cast<void**>(&d_out), size); \
in1 = reinterpret_cast<half*>(malloc(size)); \
in2 = reinterpret_cast<half*>(malloc(size)); \
out = reinterpret_cast<half*>(malloc(size)); \
hipMalloc(reinterpret_cast<void **>(&d_in1), size); \
hipMalloc(reinterpret_cast<void **>(&d_in2), size); \
hipMalloc(reinterpret_cast<void **>(&d_out), size); \
in1 = reinterpret_cast<half *>(malloc(size)); \
in2 = reinterpret_cast<half *>(malloc(size)); \
out = reinterpret_cast<half *>(malloc(size)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
hipMemcpy(d_in1, in1, size, hipMemcpyHostToDevice); \
hipMemcpy(d_in2, in2, size, hipMemcpyHostToDevice); \
hipLaunchKernelGGL(op_type, dim3(1), dim3(1), 0, 0, d_in1, d_in2, d_out); \
hipMemcpy(out, d_out, size, hipMemcpyDeviceToHost); \
EXPECT_EQ(static_cast<float>(float16(out[0])), v_out); \
free(in1); \
free(in2); \
free(out); \
hipFree(d_in1); \
hipFree(d_in2); \
hipFree(d_out); \
}
#define COMPOUND_KERNEL_LAUNCH(op_type) \
void Test##op_type(float v_in1, float v_in2, float v_out) { \
LOG(INFO) << "Test " << #op_type << " on GPU!"; \
half *in1, *in2; \
half *d_in1, *d_in2; \
int size = sizeof(half); \
hipMalloc(reinterpret_cast<void **>(&d_in1), size); \
hipMalloc(reinterpret_cast<void **>(&d_in2), size); \
in1 = reinterpret_cast<half *>(malloc(size)); \
in2 = reinterpret_cast<half *>(malloc(size)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
hipMemcpy(d_in1, in1, size, hipMemcpyHostToDevice); \
hipMemcpy(d_in2, in2, size, hipMemcpyHostToDevice); \
hipLaunchKernelGGL(op_type, dim3(1), dim3(1), 0, 0, d_in1, d_in2); \
hipMemcpy(in1, d_in1, size, hipMemcpyDeviceToHost); \
EXPECT_EQ(static_cast<float>(float16(in1[0])), v_out); \
free(in1); \
free(in2); \
hipFree(d_in1); \
hipFree(d_in2); \
}
#define COMPARISON_KERNEL_LAUNCH(op_type) \
void Test##op_type(float v_in1, float v_in2, bool v_out) { \
LOG(INFO) << "Test " << #op_type << " on GPU!"; \
half *in1, *in2; \
half *d_in1, *d_in2; \
bool *out, *d_out; \
int size = sizeof(half); \
hipMalloc(reinterpret_cast<void **>(&d_in1), size); \
hipMalloc(reinterpret_cast<void **>(&d_in2), size); \
hipMalloc(reinterpret_cast<void **>(&d_out), 1); \
in1 = reinterpret_cast<half *>(malloc(size)); \
in2 = reinterpret_cast<half *>(malloc(size)); \
out = reinterpret_cast<bool *>(malloc(1)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
hipMemcpy(d_in1, in1, size, hipMemcpyHostToDevice); \
hipMemcpy(d_in2, in2, size, hipMemcpyHostToDevice); \
hipLaunchKernelGGL(op_type, dim3(1), dim3(1), 0, 0, d_in1, d_in2, d_out); \
hipMemcpy(out, d_out, 1, hipMemcpyDeviceToHost); \
EXPECT_EQ(out[0], v_out); \
free(in1); \
free(in2); \
free(out); \
hipFree(d_in1); \
hipFree(d_in2); \
hipFree(d_out); \
}
#else
#define ARITHMETIC_KERNEL_LAUNCH(op_type) \
void Test##op_type(float v_in1, float v_in2, float v_out) { \
LOG(INFO) << "Test " << #op_type << " on GPU!"; \
half *in1, *in2, *out; \
half *d_in1, *d_in2, *d_out; \
int size = sizeof(half); \
cudaMalloc(reinterpret_cast<void **>(&d_in1), size); \
cudaMalloc(reinterpret_cast<void **>(&d_in2), size); \
cudaMalloc(reinterpret_cast<void **>(&d_out), size); \
in1 = reinterpret_cast<half *>(malloc(size)); \
in2 = reinterpret_cast<half *>(malloc(size)); \
out = reinterpret_cast<half *>(malloc(size)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
......@@ -67,10 +146,10 @@ limitations under the License. */
half *in1, *in2; \
half *d_in1, *d_in2; \
int size = sizeof(half); \
cudaMalloc(reinterpret_cast<void**>(&d_in1), size); \
cudaMalloc(reinterpret_cast<void**>(&d_in2), size); \
in1 = reinterpret_cast<half*>(malloc(size)); \
in2 = reinterpret_cast<half*>(malloc(size)); \
cudaMalloc(reinterpret_cast<void **>(&d_in1), size); \
cudaMalloc(reinterpret_cast<void **>(&d_in2), size); \
in1 = reinterpret_cast<half *>(malloc(size)); \
in2 = reinterpret_cast<half *>(malloc(size)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
......@@ -91,12 +170,12 @@ limitations under the License. */
half *d_in1, *d_in2; \
bool *out, *d_out; \
int size = sizeof(half); \
cudaMalloc(reinterpret_cast<void**>(&d_in1), size); \
cudaMalloc(reinterpret_cast<void**>(&d_in2), size); \
cudaMalloc(reinterpret_cast<void**>(&d_out), 1); \
in1 = reinterpret_cast<half*>(malloc(size)); \
in2 = reinterpret_cast<half*>(malloc(size)); \
out = reinterpret_cast<bool*>(malloc(1)); \
cudaMalloc(reinterpret_cast<void **>(&d_in1), size); \
cudaMalloc(reinterpret_cast<void **>(&d_in2), size); \
cudaMalloc(reinterpret_cast<void **>(&d_out), 1); \
in1 = reinterpret_cast<half *>(malloc(size)); \
in2 = reinterpret_cast<half *>(malloc(size)); \
out = reinterpret_cast<bool *>(malloc(1)); \
in1[0] = half(float16(v_in1)); \
in2[0] = half(float16(v_in2)); \
cudaMemcpy(d_in1, in1, size, cudaMemcpyHostToDevice); \
......@@ -111,12 +190,14 @@ limitations under the License. */
cudaFree(d_in2); \
cudaFree(d_out); \
}
#endif
#ifdef PADDLE_CUDA_FP16
namespace paddle {
namespace platform {
#if CUDA_VERSION < 9000
#if defined(PADDLE_WITH_HIP) || \
(defined(PADDLE_WITH_CUDA) && CUDA_VERSION < 9000)
ARITHMETIC_KERNEL(Add, +)
ARITHMETIC_KERNEL(Sub, -)
ARITHMETIC_KERNEL(Mul, *)
......@@ -128,21 +209,37 @@ ARITHMETIC_KERNEL_LAUNCH(Mul)
ARITHMETIC_KERNEL_LAUNCH(Div)
// Negative sign kernel
__global__ void Neg(half* in) { in[0] = -in[0]; }
__global__ void Neg(half *in) { in[0] = -in[0]; }
void TestNeg(float v_in, float v_out) {
LOG(INFO) << "Test Neg on GPU!";
half *in, *d_in;
int size = sizeof(half);
cudaMalloc(reinterpret_cast<void**>(&d_in), size);
in = reinterpret_cast<half*>(malloc(size));
#ifdef PADDLE_WITH_HIP
hipMalloc(reinterpret_cast<void **>(&d_in), size);
#else
cudaMalloc(reinterpret_cast<void **>(&d_in), size);
#endif
in = reinterpret_cast<half *>(malloc(size));
in[0] = half(float16(v_in));
#ifdef PADDLE_WITH_HIP
hipMemcpy(d_in, in, size, hipMemcpyHostToDevice);
#else
cudaMemcpy(d_in, in, size, cudaMemcpyHostToDevice);
#endif
Neg<<<1, 1>>>(d_in);
#ifdef PADDLE_WITH_HIP
hipMemcpy(in, d_in, size, hipMemcpyDeviceToHost);
#else
cudaMemcpy(in, d_in, size, cudaMemcpyDeviceToHost);
#endif
EXPECT_EQ(static_cast<float>(float16(in[0])), v_out);
free(in);
#ifdef PADDLE_WITH_HIP
hipFree(d_in);
#else
cudaFree(d_in);
#endif
}
COMPOUND_KERNEL(AddAssign, +=)
......@@ -221,7 +318,7 @@ TEST(float16, lod_tensor_on_gpu) {
framework::LoDTensor gpu_tensor;
framework::LoDTensor dst_tensor;
float16* src_ptr = src_tensor.mutable_data<float16>(
float16 *src_ptr = src_tensor.mutable_data<float16>(
framework::make_ddim({2, 2}), CPUPlace());
float16 arr[4] = {float16(1.0f), float16(0.5f), float16(0.33333f),
......@@ -238,7 +335,7 @@ TEST(float16, lod_tensor_on_gpu) {
// Sync before comparing LoDTensors
gpu_ctx.Wait();
const float16* dst_ptr = dst_tensor.data<float16>();
const float16 *dst_ptr = dst_tensor.data<float16>();
ASSERT_NE(src_ptr, dst_ptr);
for (size_t i = 0; i < 4; ++i) {
EXPECT_EQ(src_ptr[i].x, dst_ptr[i].x);
......@@ -247,7 +344,7 @@ TEST(float16, lod_tensor_on_gpu) {
template <typename T>
struct Functor {
bool operator()(const T& val) {
bool operator()(const T &val) {
return std::type_index(typeid(T)) ==
std::type_index(typeid(platform::float16));
}
......@@ -304,13 +401,13 @@ TEST(float16, cast) {
auto b = a;
{
// change semantic, keep the same value
float16 c = reinterpret_cast<float16&>(reinterpret_cast<unsigned&>(b));
float16 c = reinterpret_cast<float16 &>(reinterpret_cast<unsigned &>(b));
EXPECT_EQ(b, c);
}
{
// use uint32 low 16 bit store float16
uint32_t c = reinterpret_cast<uint32_t&>(b);
uint32_t c = reinterpret_cast<uint32_t &>(b);
float16 d;
d.x = c;
EXPECT_EQ(b, d);
......
paddle/fluid/platform/gen_comm_id_helper.cc
浏览文件 @ 34f1628c
......@@ -12,7 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#if (defined PADDLE_WITH_NCCL) || (defined PADDLE_WITH_XPU_BKCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL) || \
defined(PADDLE_WITH_XPU_BKCL)
#include "paddle/fluid/platform/gen_comm_id_helper.h"
#include <arpa/inet.h>
......@@ -336,7 +337,7 @@ void RecvBroadCastCommID(int server_fd, std::string endpoint,
template void RecvBroadCastCommID<Type>(std::string endpoint, \
std::vector<Type> * nccl_ids);
#ifdef PADDLE_WITH_NCCL
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
INSTANT_TEMPLATE(ncclUniqueId)
#endif
#ifdef PADDLE_WITH_XPU_BKCL
......
paddle/fluid/platform/gen_comm_id_helper.h
浏览文件 @ 34f1628c
......@@ -14,7 +14,8 @@ limitations under the License. */
#pragma once
#if (defined PADDLE_WITH_NCCL) || (defined PADDLE_WITH_XPU_BKCL)
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL) || \
defined(PADDLE_WITH_XPU_BKCL)
#include <functional>
#include <string>
#include <vector>
......
paddle/fluid/platform/gpu_info.cc
浏览文件 @ 34f1628c
......@@ -17,7 +17,11 @@ limitations under the License. */
#include "gflags/gflags.h"
#include "paddle/fluid/platform/cuda_device_guard.h"
#ifdef PADDLE_WITH_HIP
#include "paddle/fluid/platform/dynload/miopen.h"
#else
#include "paddle/fluid/platform/dynload/cudnn.h"
#endif
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/lock_guard_ptr.h"
#include "paddle/fluid/platform/macros.h"
......@@ -40,19 +44,34 @@ namespace platform {
int CudnnVersion() {
if (!dynload::HasCUDNN()) return -1;
#ifdef PADDLE_WITH_HIP
size_t version_major, version_minor, version_patch;
PADDLE_ENFORCE_CUDA_SUCCESS(dynload::miopenGetVersion(
&version_major, &version_minor, &version_patch));
return version_major * 100 + version_minor * 10 + version_patch;
#else
return dynload::cudnnGetVersion();
#endif
}
static int GetCUDADeviceCountImpl() {
int driverVersion = 0;
#ifdef PADDLE_WITH_HIP
hipError_t status = hipDriverGetVersion(&driverVersion);
#else
cudaError_t status = cudaDriverGetVersion(&driverVersion);
#endif
if (!(status == cudaSuccess && driverVersion != 0)) {
if (!(status == gpuSuccess && driverVersion != 0)) {
// No GPU driver
VLOG(2) << "GPU Driver Version can't be detected. No GPU driver!";
return 0;
}
#ifdef PADDLE_WITH_HIP
const auto *cuda_visible_devices = std::getenv("HIP_VISIBLE_DEVICES");
#else
const auto *cuda_visible_devices = std::getenv("CUDA_VISIBLE_DEVICES");
#endif
if (cuda_visible_devices != nullptr) {
std::string cuda_visible_devices_str(cuda_visible_devices);
if (!cuda_visible_devices_str.empty()) {
......@@ -68,12 +87,17 @@ static int GetCUDADeviceCountImpl() {
if (std::all_of(cuda_visible_devices_str.begin(),
cuda_visible_devices_str.end(),
[](char ch) { return ch == ' '; })) {
VLOG(2) << "CUDA_VISIBLE_DEVICES is set to be empty. No GPU detected.";
VLOG(2) << "CUDA_VISIBLE_DEVICES or HIP_VISIBLE_DEVICES is set to be "
"empty. No GPU detected.";
return 0;
}
}
int count;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetDeviceCount(&count));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetDeviceCount(&count));
#endif
return count;
}
......@@ -94,13 +118,24 @@ int GetCUDAComputeCapability(int id) {
id, GetCUDADeviceCount()));
int major, minor;
#ifdef PADDLE_WITH_HIP
auto major_error_code = hipDeviceGetAttribute(
&major, hipDeviceAttributeComputeCapabilityMajor, id);
auto minor_error_code = hipDeviceGetAttribute(
&minor, hipDeviceAttributeComputeCapabilityMinor, id);
#else
auto major_error_code =
cudaDeviceGetAttribute(&major, cudaDevAttrComputeCapabilityMajor, id);
auto minor_error_code =
cudaDeviceGetAttribute(&minor, cudaDevAttrComputeCapabilityMinor, id);
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(major_error_code);
PADDLE_ENFORCE_CUDA_SUCCESS(minor_error_code);
#ifdef PADDLE_WITH_HIP
return major * 100 + minor;
#else
return major * 10 + minor;
#endif
}
dim3 GetGpuMaxGridDimSize(int id) {
......@@ -111,15 +146,30 @@ dim3 GetGpuMaxGridDimSize(int id) {
id, GetCUDADeviceCount()));
dim3 ret;
int size;
#ifdef PADDLE_WITH_HIP
auto error_code_x =
hipDeviceGetAttribute(&size, hipDeviceAttributeMaxGridDimX, id);
#else
auto error_code_x = cudaDeviceGetAttribute(&size, cudaDevAttrMaxGridDimX, id);
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(error_code_x);
ret.x = size;
#ifdef PADDLE_WITH_HIP
auto error_code_y =
hipDeviceGetAttribute(&size, hipDeviceAttributeMaxGridDimY, id);
#else
auto error_code_y = cudaDeviceGetAttribute(&size, cudaDevAttrMaxGridDimY, id);
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(error_code_y);
ret.y = size;
#ifdef PADDLE_WITH_HIP
auto error_code_z =
hipDeviceGetAttribute(&size, hipDeviceAttributeMaxGridDimZ, id);
#else
auto error_code_z = cudaDeviceGetAttribute(&size, cudaDevAttrMaxGridDimZ, id);
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(error_code_z);
ret.z = size;
return ret;
......@@ -132,7 +182,11 @@ int GetCUDARuntimeVersion(int id) {
"but received id is: %d. GPU count is: %d.",
id, GetCUDADeviceCount()));
int runtime_version = 0;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipRuntimeGetVersion(&runtime_version));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaRuntimeGetVersion(&runtime_version));
#endif
return runtime_version;
}
......@@ -143,12 +197,16 @@ int GetCUDADriverVersion(int id) {
"but received id is: %d. GPU count is: %d.",
id, GetCUDADeviceCount()));
int driver_version = 0;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipDriverGetVersion(&driver_version));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaDriverGetVersion(&driver_version));
#endif
return driver_version;
}
bool TensorCoreAvailable() {
#if CUDA_VERSION >= 9000
#if !defined(PADDLE_WITH_HIP) && CUDA_VERSION >= 9000
int device = GetCurrentDeviceId();
int driver_version = GetCUDAComputeCapability(device);
return driver_version >= 70;
......@@ -164,8 +222,13 @@ int GetCUDAMultiProcessors(int id) {
"but received id is: %d. GPU count is: %d.",
id, GetCUDADeviceCount()));
int count;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
hipDeviceGetAttribute(&count, hipDeviceAttributeMultiprocessorCount, id));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
cudaDeviceGetAttribute(&count, cudaDevAttrMultiProcessorCount, id));
#endif
return count;
}
......@@ -176,8 +239,13 @@ int GetCUDAMaxThreadsPerMultiProcessor(int id) {
"but received id is: %d. GPU count is: %d.",
id, GetCUDADeviceCount()));
int count;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipDeviceGetAttribute(
&count, hipDeviceAttributeMaxThreadsPerMultiProcessor, id));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaDeviceGetAttribute(
&count, cudaDevAttrMaxThreadsPerMultiProcessor, id));
#endif
return count;
}
......@@ -188,14 +256,23 @@ int GetCUDAMaxThreadsPerBlock(int id) {
"but received id is: %d. GPU count is: %d.",
id, GetCUDADeviceCount()));
int count;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
hipDeviceGetAttribute(&count, hipDeviceAttributeMaxThreadsPerBlock, id));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
cudaDeviceGetAttribute(&count, cudaDevAttrMaxThreadsPerBlock, id));
#endif
return count;
}
int GetCurrentDeviceId() {
int device_id;
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipGetDevice(&device_id));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaGetDevice(&device_id));
#endif
return device_id;
}
......@@ -224,7 +301,11 @@ void SetDeviceId(int id) {
"Device id must be less than GPU count, "
"but received id is: %d. GPU count is: %d.",
id, GetCUDADeviceCount()));
#ifdef PADDLE_WITH_HIP
PADDLE_RETRY_CUDA_SUCCESS(hipSetDevice(id));
#else
PADDLE_RETRY_CUDA_SUCCESS(cudaSetDevice(id));
#endif
}
void GpuMemoryUsage(size_t *available, size_t *total) {
......@@ -289,46 +370,91 @@ size_t GpuMaxChunkSize() {
return max_chunk_size;
}
#ifdef PADDLE_WITH_HIP
void GpuMemcpyAsync(void *dst, const void *src, size_t count,
enum hipMemcpyKind kind, hipStream_t stream) {
PADDLE_ENFORCE_CUDA_SUCCESS(hipMemcpyAsync(dst, src, count, kind, stream));
}
#else
void GpuMemcpyAsync(void *dst, const void *src, size_t count,
enum cudaMemcpyKind kind, cudaStream_t stream) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpyAsync(dst, src, count, kind, stream));
}
#endif
#ifdef PADDLE_WITH_HIP
void GpuMemcpySync(void *dst, const void *src, size_t count,
enum hipMemcpyKind kind) {
PADDLE_ENFORCE_CUDA_SUCCESS(hipMemcpy(dst, src, count, kind));
}
#else
void GpuMemcpySync(void *dst, const void *src, size_t count,
enum cudaMemcpyKind kind) {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemcpy(dst, src, count, kind));
}
#endif
void GpuMemcpyPeerAsync(void *dst, int dst_device, const void *src,
int src_device, size_t count, cudaStream_t stream) {
int src_device, size_t count, gpuStream_t stream) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
hipMemcpyPeerAsync(dst, dst_device, src, src_device, count, stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
cudaMemcpyPeerAsync(dst, dst_device, src, src_device, count, stream));
#endif
}
void GpuMemcpyPeerSync(void *dst, int dst_device, const void *src,
int src_device, size_t count) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
hipMemcpyPeer(dst, dst_device, src, src_device, count));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(
cudaMemcpyPeer(dst, dst_device, src, src_device, count));
#endif
}
void GpuMemsetAsync(void *dst, int value, size_t count, cudaStream_t stream) {
void GpuMemsetAsync(void *dst, int value, size_t count, gpuStream_t stream) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipMemsetAsync(dst, value, count, stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaMemsetAsync(dst, value, count, stream));
#endif
}
void GpuStreamSync(cudaStream_t stream) {
void GpuStreamSync(gpuStream_t stream) {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream));
#endif
}
static void RaiseNonOutOfMemoryError(cudaError_t *status) {
static void RaiseNonOutOfMemoryError(gpuError_t *status) {
#ifdef PADDLE_WITH_HIP
if (*status == hipErrorOutOfMemory) {
*status = hipSuccess;
}
#else
if (*status == cudaErrorMemoryAllocation) {
*status = cudaSuccess;
}
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(*status);
#ifdef PADDLE_WITH_HIP
*status = hipGetLastError();
if (*status == hipErrorOutOfMemory) {
*status = hipSuccess;
}
#else
*status = cudaGetLastError();
if (*status == cudaErrorMemoryAllocation) {
*status = cudaSuccess;
}
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(*status);
}
......@@ -370,26 +496,38 @@ class RecordedCudaMallocHelper {
* or cudaSuccess would be returned, and the cudaGetLastError() flag
* would be clear.
*/
cudaError_t Malloc(void **ptr, size_t size) {
gpuError_t Malloc(void **ptr, size_t size) {
LockGuardPtr<std::mutex> lock(mtx_);
if (UNLIKELY(NeedRecord() && cur_size_ + size > limit_size_)) {
#ifdef PADDLE_WITH_HIP
return hipErrorOutOfMemory;
#else
return cudaErrorMemoryAllocation;
#endif
}
CUDADeviceGuard guard(dev_id_);
#ifdef PADDLE_WITH_HIP
auto result = hipMalloc(ptr, size);
#else
auto result = cudaMalloc(ptr, size);
if (result == cudaSuccess) {
#endif
if (result == gpuSuccess) {
if (NeedRecord()) {
cur_size_ += size;
}
STAT_INT_ADD("STAT_gpu" + std::to_string(dev_id_) + "_mem_size", size);
return cudaSuccess;
return gpuSuccess;
} else {
RaiseNonOutOfMemoryError(&result);
// Non out of memory error would be raised inside
// RaiseNonOutOfMemoryError. Therefore, we can
// return cudaErrorMemoryAllocation directly here.
// Non out of memory error would be raised inside
// RaiseNonOutOfMemoryError. Therefore, we can
// return cudaErrorMemoryAllocation directly here.
#ifdef PADDLE_WITH_HIP
return hipErrorOutOfMemory;
#else
return cudaErrorMemoryAllocation;
#endif
}
}
......@@ -404,8 +542,13 @@ class RecordedCudaMallocHelper {
// process is terminating, in which case we don't care if
// cudaFree succeeds.
CUDADeviceGuard guard(dev_id_);
#ifdef PADDLE_WITH_HIP
auto err = hipFree(ptr);
if (err != hipErrorDeinitialized) {
#else
auto err = cudaFree(ptr);
if (err != cudaErrorCudartUnloading) {
#endif
PADDLE_ENFORCE_CUDA_SUCCESS(err);
if (NeedRecord()) {
std::lock_guard<std::mutex> guard(*mtx_);
......@@ -413,7 +556,11 @@ class RecordedCudaMallocHelper {
}
STAT_INT_SUB("STAT_gpu" + std::to_string(dev_id_) + "_mem_size", size);
} else {
#ifdef PADDLE_WITH_HIP
hipGetLastError(); // clear the error flag when hipErrorDeinitialized
#else
cudaGetLastError(); // clear the error flag when cudaErrorCudartUnloading
#endif
}
}
......@@ -421,8 +568,12 @@ class RecordedCudaMallocHelper {
size_t *actual_total) {
{
CUDADeviceGuard guard(dev_id_);
#ifdef PADDLE_WITH_HIP
auto result = hipMemGetInfo(actual_avail, actual_total);
#else
auto result = cudaMemGetInfo(actual_avail, actual_total);
if (result != cudaSuccess) {
#endif
if (result != gpuSuccess) {
*actual_avail = 0;
}
RaiseNonOutOfMemoryError(&result);
......@@ -458,13 +609,13 @@ class RecordedCudaMallocHelper {
static std::once_flag once_flag_;
static std::vector<std::unique_ptr<RecordedCudaMallocHelper>> instances_;
};
}; // NOLINT
std::once_flag RecordedCudaMallocHelper::once_flag_;
std::vector<std::unique_ptr<RecordedCudaMallocHelper>>
RecordedCudaMallocHelper::instances_;
cudaError_t RecordedCudaMalloc(void **ptr, size_t size, int dev_id) {
gpuError_t RecordedCudaMalloc(void **ptr, size_t size, int dev_id) {
return RecordedCudaMallocHelper::Instance(dev_id)->Malloc(ptr, size);
}
......
paddle/fluid/platform/gpu_info.h
浏览文件 @ 34f1628c
......@@ -15,11 +15,19 @@ limitations under the License. */
#pragma once
#ifdef PADDLE_WITH_CUDA
#include <cuda_runtime.h>
#endif
#ifdef PADDLE_WITH_HIP
#include <hip/hip_runtime.h>
#endif
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
// Note: this header for simplify HIP and CUDA type string
#include <stddef.h>
#include <string>
#include <vector>
#include "paddle/fluid/platform/type_defs.h"
namespace paddle {
namespace platform {
......@@ -86,28 +94,36 @@ size_t GpuMaxChunkSize();
//! Copy memory from address src to dst asynchronously.
void GpuMemcpyAsync(void *dst, const void *src, size_t count,
#ifdef PADDLE_WITH_HIP
enum hipMemcpyKind kind, hipStream_t stream);
#else
enum cudaMemcpyKind kind, cudaStream_t stream);
#endif
//! Copy memory from address src to dst synchronously.
void GpuMemcpySync(void *dst, const void *src, size_t count,
#ifdef PADDLE_WITH_HIP
enum hipMemcpyKind kind);
#else
enum cudaMemcpyKind kind);
#endif
//! Copy memory from one device to another device asynchronously.
void GpuMemcpyPeerAsync(void *dst, int dst_device, const void *src,
int src_device, size_t count, cudaStream_t stream);
int src_device, size_t count, gpuStream_t stream);
//! Copy memory from one device to another device synchronously.
void GpuMemcpyPeerSync(void *dst, int dst_device, const void *src,
int src_device, size_t count);
//! Set memory dst with value count size asynchronously
void GpuMemsetAsync(void *dst, int value, size_t count, cudaStream_t stream);
void GpuMemsetAsync(void *dst, int value, size_t count, gpuStream_t stream);
//! Blocks until stream has completed all operations.
void GpuStreamSync(cudaStream_t stream);
void GpuStreamSync(gpuStream_t stream);
//! CudaMalloc with recorded info
cudaError_t RecordedCudaMalloc(void **ptr, size_t size, int dev_id);
gpuError_t RecordedCudaMalloc(void **ptr, size_t size, int dev_id);
//! CudaFree with recorded info
void RecordedCudaFree(void *p, size_t size, int dev_id);
......
paddle/fluid/platform/gpu_launch_config.h
浏览文件 @ 34f1628c
......@@ -16,9 +16,13 @@
#pragma once
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#ifdef PADDLE_WITH_CUDA
#include <cuda_runtime.h>
#else
#include <hip/hip_runtime.h>
#endif
#include <stddef.h>
#include <algorithm>
#include <string>
......
paddle/fluid/platform/nccl_helper.h
浏览文件 @ 34f1628c
......@@ -14,7 +14,7 @@
#pragma once
#ifdef PADDLE_WITH_NCCL
#if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
#include <stdio.h>
#include <memory>
#include <string>
......@@ -25,7 +25,12 @@
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/platform/collective_helper.h"
#ifdef PADDLE_WITH_NCCL
#include "paddle/fluid/platform/dynload/nccl.h"
#endif
#ifdef PADDLE_WITH_RCCL
#include "paddle/fluid/platform/dynload/rccl.h"
#endif
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/float16.h"
......@@ -81,7 +86,7 @@ struct NCCLContext {
explicit NCCLContext(int dev_id)
: ctx_(new CUDADeviceContext(CUDAPlace(dev_id))), comm_{nullptr} {}
cudaStream_t stream() const { return ctx_->stream(); }
gpuStream_t stream() const { return ctx_->stream(); }
ncclComm_t comm() const { return comm_; }
int device_id() const {
......
paddle/fluid/platform/place.h
浏览文件 @ 34f1628c
......@@ -154,7 +154,7 @@ struct PlaceVisitorWrapper
}
typename Visitor::result_type operator()(const CUDAPlace &cuda) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
return visitor_(cuda);
#else
PADDLE_THROW(platform::errors::Unavailable(
......@@ -165,7 +165,7 @@ struct PlaceVisitorWrapper
typename Visitor::result_type operator()(
const CUDAPinnedPlace &cuda_pinned) const {
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
return visitor_(cuda_pinned);
#else
PADDLE_THROW(platform::errors::Unavailable(
......
paddle/fluid/platform/profiler.cc
浏览文件 @ 34f1628c
......@@ -206,7 +206,7 @@ void EnableProfiler(ProfilerState state) {
g_state = state;
should_send_profile_state = true;
GetDeviceTracer()->Enable();
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
if (g_state == ProfilerState::kCUDA || g_state == ProfilerState::kAll ||
g_state == ProfilerState::kCPU) {
// Generate some dummy events first to reduce the startup overhead.
......
paddle/fluid/platform/profiler.cu
浏览文件 @ 34f1628c
......@@ -12,7 +12,14 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#ifdef PADDLE_WITH_CUDA
#include <cuda.h>
#endif
#ifdef PADDLE_WITH_HIP
#include <hip/hip_runtime.h>
#endif
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
......@@ -31,6 +38,21 @@ static void ForEachDevice(std::function<void(int)> func) {
}
void DummyKernelAndEvent() {
#ifdef PADDLE_WITH_HIP
for (int i = 0; i < 5; i++) {
ForEachDevice([](int d) {
platform::SetDeviceId(d);
hipStream_t stream;
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamCreate(&stream));
Mark("_cuda_startup_");
int *ptr;
PADDLE_ENFORCE_CUDA_SUCCESS(hipMalloc(&ptr, sizeof(int)));
hipLaunchKernelGGL(DummyKernel, dim3(1), dim3(1), 0, stream, ptr);
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream));
PADDLE_ENFORCE_CUDA_SUCCESS(hipFree(ptr));
});
}
#else
for (int i = 0; i < 5; i++) {
ForEachDevice([](int d) {
platform::SetDeviceId(d);
......@@ -44,6 +66,7 @@ void DummyKernelAndEvent() {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaFree(ptr));
});
}
#endif
}
} // namespace platform
......
paddle/fluid/platform/profiler.h
浏览文件 @ 34f1628c
......@@ -28,7 +28,7 @@ limitations under the License. */
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/event.h"
#include "paddle/fluid/platform/place.h"
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#include "paddle/fluid/platform/gpu_info.h"
#endif
namespace paddle {
......@@ -220,7 +220,7 @@ std::string OpName(const framework::VariableNameMap& name_map,
const std::string& type_name);
void SetTracerOption(TracerOption option);
platform::TracerOption GetTracerOption();
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
void DummyKernelAndEvent();
#endif
......
paddle/fluid/platform/profiler_helper.h
浏览文件 @ 34f1628c
......@@ -31,6 +31,9 @@ limitations under the License. */
#ifdef PADDLE_WITH_CUDA
#include <cuda.h>
#endif // PADDLE_WITH_CUDA
#ifdef PADDLE_WITH_HIP
#include <hip/hip_runtime.h>
#endif
namespace paddle {
namespace platform {
......@@ -122,6 +125,13 @@ void SynchronizeAllDevice() {
PADDLE_ENFORCE_CUDA_SUCCESS(cudaDeviceSynchronize());
}
#endif
#ifdef PADDLE_WITH_HIP
int count = GetCUDADeviceCount();
for (int i = 0; i < count; i++) {
SetDeviceId(i);
PADDLE_ENFORCE_CUDA_SUCCESS(hipDeviceSynchronize());
}
#endif
}
// Print results
......@@ -300,7 +310,7 @@ void SetEvent(bool merge_thread, const Event &analyze_event,
if (rit != pushed_events->rend()) {
double event_time = 0;
double gpu_time = 0.0f;
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
gpu_time = rit->CudaElapsedMs(analyze_event);
#endif
double cpu_time = rit->CpuElapsedMs(analyze_event);
......
paddle/fluid/platform/profiler_test.cc
浏览文件 @ 34f1628c
......@@ -122,7 +122,7 @@ TEST(RecordEvent, RecordEvent) {
if (events[i][j].name() == "_start_profiler_") ++start_profiler_count;
if (events[i][j].name() == "push") {
EXPECT_EQ(events[i][j + 1].name(), "pop");
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
EXPECT_GT(events[i][j].CudaElapsedMs(events[i][j + 1]), 0);
#else
EXPECT_GT(events[i][j].CpuElapsedMs(events[i][j + 1]), 0);
......@@ -146,3 +146,13 @@ TEST(TMP, stream_wait) {
cudaStreamSynchronize(stream);
}
#endif
#ifdef PADDLE_WITH_HIP
TEST(TMP, stream_wait) {
hipStream_t stream;
hipStreamCreate(&stream);
hipStreamSynchronize(stream);
hipStreamSynchronize(stream);
hipStreamSynchronize(stream);
}
#endif
paddle/fluid/platform/stream_callback_manager.cc
浏览文件 @ 34f1628c
......@@ -18,7 +18,10 @@
namespace paddle {
namespace platform {
#if CUDA_VERSION >= 10000
#ifdef PADDLE_WITH_HIP
static void StreamCallbackFunc(gpuStream_t stream, gpuError_t status,
void *user_data)
#elif CUDA_VERSION >= 10000
static void CUDART_CB StreamCallbackFunc(void *user_data)
#else
static void CUDART_CB StreamCallbackFunc(cudaStream_t stream,
......@@ -30,7 +33,7 @@ static void CUDART_CB StreamCallbackFunc(cudaStream_t stream,
(*func)();
}
StreamCallbackManager::StreamCallbackManager(const cudaStream_t stream)
StreamCallbackManager::StreamCallbackManager(const gpuStream_t stream)
: stream_(stream), thread_pool_(1) {}
void StreamCallbackManager::AddCallback(std::function<void()> callback) const {
......@@ -42,7 +45,10 @@ void StreamCallbackManager::AddCallback(std::function<void()> callback) const {
(*callback_func)();
});
});
#if CUDA_VERSION >= 10000
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(
hipStreamAddCallback(stream_, StreamCallbackFunc, func, 0));
#elif CUDA_VERSION >= 10000
PADDLE_ENFORCE_CUDA_SUCCESS(
cudaLaunchHostFunc(stream_, StreamCallbackFunc, func));
#else
......@@ -52,7 +58,11 @@ void StreamCallbackManager::AddCallback(std::function<void()> callback) const {
}
void StreamCallbackManager::Wait() const {
#ifdef PADDLE_WITH_HIP
PADDLE_ENFORCE_CUDA_SUCCESS(hipStreamSynchronize(stream_));
#else
PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(stream_));
#endif
{
std::lock_guard<std::mutex> lock(mtx_);
if (last_future_.valid()) {
......
paddle/fluid/platform/stream_callback_manager.h
浏览文件 @ 34f1628c
......@@ -15,8 +15,16 @@
#pragma once
#include <ThreadPool.h>
#ifdef PADDLE_WITH_CUDA
#include <cuda.h>
#include <cuda_runtime.h>
#endif
#ifdef PADDLE_WITH_HIP
#include <hip/hip_runtime.h>
#endif
#include <functional>
#include <future> // NOLINT
#include <memory>
......@@ -31,7 +39,7 @@ namespace platform {
// Make StreamCallbackManager thread-safe
class StreamCallbackManager {
public:
explicit StreamCallbackManager(const cudaStream_t stream);
explicit StreamCallbackManager(const gpuStream_t stream);
~StreamCallbackManager() = default;
......@@ -40,7 +48,7 @@ class StreamCallbackManager {
void Wait() const;
private:
const cudaStream_t stream_;
const gpuStream_t stream_;
mutable ::ThreadPool thread_pool_;
mutable std::mutex mtx_;
mutable std::future<void> last_future_;
......
paddle/fluid/platform/test_limit_gpu_memory.cu
浏览文件 @ 34f1628c
......@@ -40,24 +40,36 @@ TEST(test_record_malloc, test_limit_gpu_memory) {
RecordedCudaMemGetInfo(&avail, &total, &actual_avail, &actual_total,
DEVICE_ID);
ASSERT_EQ(total, limit);
ASSERT_EQ(cudaGetLastError(), cudaSuccess);
#ifdef PADDLE_WITH_HIP
ASSERT_EQ(hipGetLastError(), gpuSuccess);
#else
ASSERT_EQ(cudaGetLastError(), gpuSuccess);
#endif
}
{
CUDADeviceGuard guard(DEVICE_ID);
GpuMemoryUsage(&avail, &total);
ASSERT_EQ(total, limit);
ASSERT_EQ(cudaGetLastError(), cudaSuccess);
#ifdef PADDLE_WITH_HIP
ASSERT_EQ(hipGetLastError(), gpuSuccess);
#else
ASSERT_EQ(cudaGetLastError(), gpuSuccess);
#endif
}
cudaError_t err = cudaSuccess;
gpuError_t err = gpuSuccess;
void *p1 = nullptr;
size_t size1 = limit / 4 * 3;
{
err = platform::RecordedCudaMalloc(&p1, size1, DEVICE_ID);
ASSERT_EQ(err, cudaSuccess);
ASSERT_EQ(cudaGetLastError(), cudaSuccess);
ASSERT_EQ(err, gpuSuccess);
#ifdef PADDLE_WITH_HIP
ASSERT_EQ(hipGetLastError(), gpuSuccess);
#else
ASSERT_EQ(cudaGetLastError(), gpuSuccess);
#endif
ASSERT_NE(p1, nullptr);
ASSERT_EQ(RecordedCudaMallocSize(DEVICE_ID), size1);
......@@ -67,8 +79,13 @@ TEST(test_record_malloc, test_limit_gpu_memory) {
size_t size2 = limit / 2;
{
err = platform::RecordedCudaMalloc(&p2, size2, DEVICE_ID);
#ifdef PADDLE_WITH_HIP
ASSERT_EQ(err, hipErrorOutOfMemory);
ASSERT_EQ(hipGetLastError(), gpuSuccess);
#else
ASSERT_EQ(err, cudaErrorMemoryAllocation);
ASSERT_EQ(cudaGetLastError(), cudaSuccess);
ASSERT_EQ(cudaGetLastError(), gpuSuccess);
#endif
ASSERT_EQ(p2, nullptr);
ASSERT_EQ(RecordedCudaMallocSize(DEVICE_ID), size1);
......@@ -81,8 +98,12 @@ TEST(test_record_malloc, test_limit_gpu_memory) {
{
err = platform::RecordedCudaMalloc(&p2, size2, DEVICE_ID);
ASSERT_EQ(err, cudaSuccess);
ASSERT_EQ(err, gpuSuccess);
#ifdef PADDLE_WITH_HIP
ASSERT_EQ(hipGetLastError(), hipSuccess);
#else
ASSERT_EQ(cudaGetLastError(), cudaSuccess);
#endif
ASSERT_NE(p2, nullptr);
ASSERT_EQ(RecordedCudaMallocSize(DEVICE_ID), size2);
}
......
paddle/fluid/platform/transform.h
浏览文件 @ 34f1628c
......@@ -22,7 +22,7 @@ limitations under the License. */
#include "paddle/fluid/platform/hostdevice.h"
#include "paddle/fluid/platform/place.h"
#ifdef __NVCC__
#if defined(__NVCC__) || defined(__HIPCC__)
#include <thrust/execution_policy.h>
#include <thrust/transform.h>
#include "paddle/fluid/platform/details/cuda_transform_iterator_cast.h"
......@@ -76,7 +76,7 @@ struct Transform<platform::CPUDeviceContext> {
}
};
#ifdef __NVCC__
#if defined(__NVCC__) || defined(__HIPCC__)
template <>
struct Transform<platform::CUDADeviceContext> {
template <typename InputIter, typename OutputIter, typename UnaryOperation>
......@@ -86,10 +86,17 @@ struct Transform<platform::CUDADeviceContext> {
PADDLE_ENFORCE_EQ(is_gpu_place(place), true,
platform::errors::PreconditionNotMet(
"The CUDA Transform must be used in GPU place."));
#ifdef __HIPCC__
thrust::transform(thrust::hip::par.on(context.stream()),
details::CastToCUDATransformIterator(first),
details::CastToCUDATransformIterator(last),
details::CastToCUDATransformIterator(result), op);
#else
thrust::transform(thrust::cuda::par.on(context.stream()),
details::CastToCUDATransformIterator(first),
details::CastToCUDATransformIterator(last),
details::CastToCUDATransformIterator(result), op);
#endif
}
template <typename InputIter1, typename InputIter2, typename OutputIter,
......@@ -101,11 +108,19 @@ struct Transform<platform::CUDADeviceContext> {
PADDLE_ENFORCE_EQ(is_gpu_place(place), true,
platform::errors::PreconditionNotMet(
"The CUDA Transform must be used in GPU place."));
#ifdef __HIPCC__
thrust::transform(thrust::hip::par.on(context.stream()),
details::CastToCUDATransformIterator(first1),
details::CastToCUDATransformIterator(last1),
details::CastToCUDATransformIterator(first2),
details::CastToCUDATransformIterator(result), op);
#else
thrust::transform(thrust::cuda::par.on(context.stream()),
details::CastToCUDATransformIterator(first1),
details::CastToCUDATransformIterator(last1),
details::CastToCUDATransformIterator(first2),
details::CastToCUDATransformIterator(result), op);
#endif
}
};
#endif
......
paddle/fluid/platform/variant.h
浏览文件 @ 34f1628c
......@@ -32,7 +32,7 @@ limitations under the License. */
// BOOST_NO_CXX11_VARIADIC_TEMPLATES on gcc/clang to generate same
// function symbols. For details,
// https://github.com/PaddlePaddle/Paddle/issues/3386
#ifdef PADDLE_WITH_CUDA
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
#ifndef BOOST_NO_CXX11_VARIADIC_TEMPLATES
#define BOOST_NO_CXX11_VARIADIC_TEMPLATES
#endif
......
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