This repository has been archived on 2023-10-09. You can view files and clone it, but cannot push or open issues or pull requests.
Files
blender-archive/intern/opensubdiv/internal/opensubdiv_device_context_cuda.cc
Campbell Barton e12c08e8d1 ClangFormat: apply to source, most of intern
Apply clang format as proposed in T53211.

For details on usage and instructions for migrating branches
without conflicts, see:

https://wiki.blender.org/wiki/Tools/ClangFormat
2019-04-17 06:21:24 +02:00

235 lines
7.3 KiB
C++

// Adopted from OpenSubdiv with the following license:
//
// Copyright 2015 Pixar
//
// Licensed under the Apache License, Version 2.0 (the "Apache License")
// with the following modification; you may not use this file except in
// compliance with the Apache License and the following modification to it:
// Section 6. Trademarks. is deleted and replaced with:
//
// 6. Trademarks. This License does not grant permission to use the trade
// names, trademarks, service marks, or product names of the Licensor
// and its affiliates, except as required to comply with Section 4(c) of
// the License and to reproduce the content of the NOTICE file.
//
// You may obtain a copy of the Apache License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the Apache License with the above modification is
// distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, either express or implied. See the Apache License for the specific
// language governing permissions and limitations under the Apache License.
#ifdef OPENSUBDIV_HAS_CUDA
# ifdef _MSC_VER
# include <iso646.h>
# endif
# include "opensubdiv_device_context_cuda.h"
# if defined(_WIN32)
# include <windows.h>
# elif defined(__APPLE__)
# include <OpenGL/OpenGL.h>
# else
# include <GL/glx.h>
# include <X11/Xlib.h>
# endif
# include <cuda.h>
# include <cuda_gl_interop.h>
# include <cuda_runtime_api.h>
# include <cstdio>
# include "internal/opensubdiv_util.h"
# define message(fmt, ...)
// #define message(fmt, ...) fprintf(stderr, fmt, __VA_ARGS__)
# define error(fmt, ...) fprintf(stderr, fmt, __VA_ARGS__)
namespace {
int getCudaDeviceForCurrentGLContext()
{
// Find and use the CUDA device for the current GL context
unsigned int interop_device_count = 0;
int interopDevices[1];
cudaError_t status = cudaGLGetDevices(
&interop_device_count, interopDevices, 1, cudaGLDeviceListCurrentFrame);
if (status == cudaErrorNoDevice || interop_device_count != 1) {
message("CUDA no interop devices found.\n");
return 0;
}
int device = interopDevices[0];
# if defined(_WIN32)
return device;
# elif defined(__APPLE__)
return device;
# else // X11
Display *display = glXGetCurrentDisplay();
int screen = DefaultScreen(display);
if (device != screen) {
error(
"The CUDA interop device (%d) does not match "
"the screen used by the current GL context (%d), "
"which may cause slow performance on systems "
"with multiple GPU devices.",
device,
screen);
}
message("CUDA init using device for current GL context: %d\n", device);
return device;
# endif
}
// Beginning of GPU Architecture definitions.
int convertSMVer2Cores_local(int major, int minor)
{
// Defines for GPU Architecture types (using the SM version to determine
// the # of cores per SM
typedef struct {
int SM; // 0xMm (hexidecimal notation),
// M = SM Major version,
// and m = SM minor version
int Cores;
} sSMtoCores;
sSMtoCores nGpuArchCoresPerSM[] = {{0x10, 8}, // Tesla Generation (SM 1.0) G80 class.
{0x11, 8}, // Tesla Generation (SM 1.1) G8x class.
{0x12, 8}, // Tesla Generation (SM 1.2) G9x class.
{0x13, 8}, // Tesla Generation (SM 1.3) GT200 class.
{0x20, 32}, // Fermi Generation (SM 2.0) GF100 class.
{0x21, 48}, // Fermi Generation (SM 2.1) GF10x class.
{0x30, 192}, // Fermi Generation (SM 3.0) GK10x class.
{-1, -1}};
int index = 0;
while (nGpuArchCoresPerSM[index].SM != -1) {
if (nGpuArchCoresPerSM[index].SM == ((major << 4) + minor)) {
return nGpuArchCoresPerSM[index].Cores;
}
index++;
}
printf("MapSMtoCores undefined SMversion %d.%d!\n", major, minor);
return -1;
}
// This function returns the best GPU (with maximum GFLOPS).
int cutGetMaxGflopsDeviceId()
{
int current_device = 0, sm_per_multiproc = 0;
int max_compute_perf = 0, max_perf_device = -1;
int device_count = 0, best_SM_arch = 0;
int compat_major, compat_minor;
cuDeviceGetCount(&device_count);
// Find the best major SM Architecture GPU device.
while (current_device < device_count) {
cuDeviceComputeCapability(&compat_major, &compat_minor, current_device);
if (compat_major > 0 && compat_major < 9999) {
best_SM_arch = max(best_SM_arch, compat_major);
}
current_device++;
}
// Find the best CUDA capable GPU device.
current_device = 0;
while (current_device < device_count) {
cuDeviceComputeCapability(&compat_major, &compat_minor, current_device);
if (compat_major == 9999 && compat_minor == 9999) {
sm_per_multiproc = 1;
}
else {
sm_per_multiproc = convertSMVer2Cores_local(compat_major, compat_minor);
}
int multi_processor_count;
cuDeviceGetAttribute(
&multi_processor_count, CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, current_device);
int clock_rate;
cuDeviceGetAttribute(&clock_rate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE, current_device);
int compute_perf = multi_processor_count * sm_per_multiproc * clock_rate;
if (compute_perf > max_compute_perf) {
/* If we find GPU with SM major > 2, search only these */
if (best_SM_arch > 2) {
/* If our device==dest_SM_arch, choose this, or else pass. */
if (compat_major == best_SM_arch) {
max_compute_perf = compute_perf;
max_perf_device = current_device;
}
}
else {
max_compute_perf = compute_perf;
max_perf_device = current_device;
}
}
++current_device;
}
return max_perf_device;
}
} // namespace
bool CudaDeviceContext::HAS_CUDA_VERSION_4_0()
{
# ifdef OPENSUBDIV_HAS_CUDA
static bool cuda_initialized = false;
static bool cuda_load_success = true;
if (!cuda_initialized) {
cuda_initialized = true;
# ifdef OPENSUBDIV_HAS_CUEW
cuda_load_success = cuewInit(CUEW_INIT_CUDA) == CUEW_SUCCESS;
if (!cuda_load_success) {
fprintf(stderr, "Loading CUDA failed.\n");
}
# endif
// Need to initialize CUDA here so getting device
// with the maximum FPLOS works fine.
if (cuInit(0) == CUDA_SUCCESS) {
// This is to deal with cases like NVidia Optimus,
// when there might be CUDA library installed but
// NVidia card is not being active.
if (cutGetMaxGflopsDeviceId() < 0) {
cuda_load_success = false;
}
}
else {
cuda_load_success = false;
}
}
return cuda_load_success;
# else
return false;
# endif
}
CudaDeviceContext::CudaDeviceContext() : initialized_(false)
{
}
CudaDeviceContext::~CudaDeviceContext()
{
cudaDeviceReset();
}
bool CudaDeviceContext::Initialize()
{
// See if any cuda device is available.
int device_count = 0;
cudaGetDeviceCount(&device_count);
message("CUDA device count: %d\n", device_count);
if (device_count <= 0) {
return false;
}
cudaGLSetGLDevice(getCudaDeviceForCurrentGLContext());
initialized_ = true;
return true;
}
bool CudaDeviceContext::IsInitialized() const
{
return initialized_;
}
#endif // OPENSUBDIV_HAS_CUDA