[Bf-blender-cvs] [b586f801fc9] master: Cycles: Improve CUDA and OptiX error reporting in the viewport
Patrick Mours
noreply at git.blender.org
Fri Jun 12 18:26:42 CEST 2020
Commit: b586f801fc921f9f420260fb3ff4f26cb6773157
Author: Patrick Mours
Date: Fri Jun 12 16:42:49 2020 +0200
Branches: master
https://developer.blender.org/rBb586f801fc921f9f420260fb3ff4f26cb6773157
Cycles: Improve CUDA and OptiX error reporting in the viewport
This patch makes the infamous "Cancel" error in the viewport a thing of the past. Instead it
now shows a more useful error message and streamlines the error handling process in CUDA.
Reviewed By: brecht
Differential Revision: https://developer.blender.org/D8008
===================================================================
M intern/cycles/device/cuda/device_cuda.h
M intern/cycles/device/cuda/device_cuda_impl.cpp
M intern/cycles/device/device_optix.cpp
M intern/cycles/render/session.cpp
===================================================================
diff --git a/intern/cycles/device/cuda/device_cuda.h b/intern/cycles/device/cuda/device_cuda.h
index 9f31ed12cf4..1aa2fdd0967 100644
--- a/intern/cycles/device/cuda/device_cuda.h
+++ b/intern/cycles/device/cuda/device_cuda.h
@@ -100,11 +100,7 @@ class CUDADevice : public Device {
virtual BVHLayoutMask get_bvh_layout_mask() const;
- void cuda_error_documentation();
-
- bool cuda_error_(CUresult result, const string &stmt);
-
- void cuda_error_message(const string &message);
+ void set_error(const string &error) override;
CUDADevice(DeviceInfo &info, Stats &stats, Profiler &profiler, bool background_);
diff --git a/intern/cycles/device/cuda/device_cuda_impl.cpp b/intern/cycles/device/cuda/device_cuda_impl.cpp
index 64c7f5e7d34..7aa63ff48c3 100644
--- a/intern/cycles/device/cuda/device_cuda_impl.cpp
+++ b/intern/cycles/device/cuda/device_cuda_impl.cpp
@@ -135,8 +135,10 @@ BVHLayoutMask CUDADevice::get_bvh_layout_mask() const
return BVH_LAYOUT_BVH2;
}
-void CUDADevice::cuda_error_documentation()
+void CUDADevice::set_error(const string &error)
{
+ Device::set_error(error);
+
if (first_error) {
fprintf(stderr, "\nRefer to the Cycles GPU rendering documentation for possible solutions:\n");
fprintf(stderr,
@@ -148,42 +150,13 @@ void CUDADevice::cuda_error_documentation()
# define cuda_assert(stmt) \
{ \
CUresult result = stmt; \
-\
if (result != CUDA_SUCCESS) { \
- string message = string_printf( \
- "CUDA error: %s in %s, line %d", cuewErrorString(result), #stmt, __LINE__); \
- if (error_msg == "") \
- error_msg = message; \
- fprintf(stderr, "%s\n", message.c_str()); \
- /*cuda_abort();*/ \
- cuda_error_documentation(); \
+ const char *name = cuewErrorString(result); \
+ set_error(string_printf("%s in %s (device_cuda_impl.cpp:%d)", name, #stmt, __LINE__)); \
} \
} \
(void)0
-bool CUDADevice::cuda_error_(CUresult result, const string &stmt)
-{
- if (result == CUDA_SUCCESS)
- return false;
-
- string message = string_printf("CUDA error at %s: %s", stmt.c_str(), cuewErrorString(result));
- if (error_msg == "")
- error_msg = message;
- fprintf(stderr, "%s\n", message.c_str());
- cuda_error_documentation();
- return true;
-}
-
-# define cuda_error(stmt) cuda_error_(stmt, # stmt)
-
-void CUDADevice::cuda_error_message(const string &message)
-{
- if (error_msg == "")
- error_msg = message;
- fprintf(stderr, "%s\n", message.c_str());
- cuda_error_documentation();
-}
-
CUDADevice::CUDADevice(DeviceInfo &info, Stats &stats, Profiler &profiler, bool background_)
: Device(info, stats, profiler, background_), texture_info(this, "__texture_info", MEM_GLOBAL)
{
@@ -212,12 +185,19 @@ CUDADevice::CUDADevice(DeviceInfo &info, Stats &stats, Profiler &profiler, bool
functions.loaded = false;
/* Intialize CUDA. */
- if (cuda_error(cuInit(0)))
+ CUresult result = cuInit(0);
+ if (result != CUDA_SUCCESS) {
+ set_error(string_printf("Failed to initialize CUDA runtime (%s)", cuewErrorString(result)));
return;
+ }
/* Setup device and context. */
- if (cuda_error(cuDeviceGet(&cuDevice, cuDevId)))
+ result = cuDeviceGet(&cuDevice, cuDevId);
+ if (result != CUDA_SUCCESS) {
+ set_error(string_printf("Failed to get CUDA device handle from ordinal (%s)",
+ cuewErrorString(result)));
return;
+ }
/* CU_CTX_MAP_HOST for mapping host memory when out of device memory.
* CU_CTX_LMEM_RESIZE_TO_MAX for reserving local memory ahead of render,
@@ -235,8 +215,6 @@ CUDADevice::CUDADevice(DeviceInfo &info, Stats &stats, Profiler &profiler, bool
}
/* Create context. */
- CUresult result;
-
if (background) {
result = cuCtxCreate(&cuContext, ctx_flags, cuDevice);
}
@@ -249,8 +227,10 @@ CUDADevice::CUDADevice(DeviceInfo &info, Stats &stats, Profiler &profiler, bool
}
}
- if (cuda_error_(result, "cuCtxCreate"))
+ if (result != CUDA_SUCCESS) {
+ set_error(string_printf("Failed to create CUDA context (%s)", cuewErrorString(result)));
return;
+ }
int major, minor;
cuDeviceGetAttribute(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, cuDevId);
@@ -280,10 +260,8 @@ bool CUDADevice::support_device(const DeviceRequestedFeatures & /*requested_feat
/* We only support sm_30 and above */
if (major < 3) {
- cuda_error_message(
- string_printf("CUDA device supported only with compute capability 3.0 or up, found %d.%d.",
- major,
- minor));
+ set_error(string_printf(
+ "CUDA backend requires compute capability 3.0 or up, but found %d.%d.", major, minor));
return false;
}
@@ -319,13 +297,19 @@ bool CUDADevice::check_peer_access(Device *peer_device)
// Enable peer access in both directions
{
const CUDAContextScope scope(this);
- if (cuda_error(cuCtxEnablePeerAccess(peer_device_cuda->cuContext, 0))) {
+ CUresult result = cuCtxEnablePeerAccess(peer_device_cuda->cuContext, 0);
+ if (result != CUDA_SUCCESS) {
+ set_error(string_printf("Failed to enable peer access on CUDA context (%s)",
+ cuewErrorString(result)));
return false;
}
}
{
const CUDAContextScope scope(peer_device_cuda);
- if (cuda_error(cuCtxEnablePeerAccess(cuContext, 0))) {
+ CUresult result = cuCtxEnablePeerAccess(cuContext, 0);
+ if (result != CUDA_SUCCESS) {
+ set_error(string_printf("Failed to enable peer access on CUDA context (%s)",
+ cuewErrorString(result)));
return false;
}
}
@@ -432,14 +416,14 @@ string CUDADevice::compile_kernel(const DeviceRequestedFeatures &requested_featu
# ifdef _WIN32
if (!use_adaptive_compilation() && have_precompiled_kernels()) {
if (major < 3) {
- cuda_error_message(
- string_printf("CUDA device requires compute capability 3.0 or up, "
- "found %d.%d. Your GPU is not supported.",
+ set_error(
+ string_printf("CUDA backend requires compute capability 3.0 or up, but found %d.%d. "
+ "Your GPU is not supported.",
major,
minor));
}
else {
- cuda_error_message(
+ set_error(
string_printf("CUDA binary kernel for this graphics card compute "
"capability (%d.%d) not found.",
major,
@@ -452,7 +436,7 @@ string CUDADevice::compile_kernel(const DeviceRequestedFeatures &requested_featu
/* Compile. */
const char *const nvcc = cuewCompilerPath();
if (nvcc == NULL) {
- cuda_error_message(
+ set_error(
"CUDA nvcc compiler not found. "
"Install CUDA toolkit in default location.");
return string();
@@ -504,7 +488,7 @@ string CUDADevice::compile_kernel(const DeviceRequestedFeatures &requested_featu
command = "call " + command;
# endif
if (system(command.c_str()) != 0) {
- cuda_error_message(
+ set_error(
"Failed to execute compilation command, "
"see console for details.");
return string();
@@ -512,7 +496,7 @@ string CUDADevice::compile_kernel(const DeviceRequestedFeatures &requested_featu
/* Verify if compilation succeeded */
if (!path_exists(cubin)) {
- cuda_error_message(
+ set_error(
"CUDA kernel compilation failed, "
"see console for details.");
return string();
@@ -565,16 +549,19 @@ bool CUDADevice::load_kernels(const DeviceRequestedFeatures &requested_features)
else
result = CUDA_ERROR_FILE_NOT_FOUND;
- if (cuda_error_(result, "cuModuleLoad"))
- cuda_error_message(string_printf("Failed loading CUDA kernel %s.", cubin.c_str()));
+ if (result != CUDA_SUCCESS)
+ set_error(string_printf(
+ "Failed to load CUDA kernel from '%s' (%s)", cubin.c_str(), cuewErrorString(result)));
if (path_read_text(filter_cubin, cubin_data))
result = cuModuleLoadData(&cuFilterModule, cubin_data.c_str());
else
result = CUDA_ERROR_FILE_NOT_FOUND;
- if (cuda_error_(result, "cuModuleLoad"))
- cuda_error_message(string_printf("Failed loading CUDA kernel %s.", filter_cubin.c_str()));
+ if (result != CUDA_SUCCESS)
+ set_error(string_printf("Failed to load CUDA kernel from '%s' (%s)",
+ filter_cubin.c_str(),
+ cuewErrorString(result)));
if (result == CUDA_SUCCESS) {
reserve_local_memory(requested_features);
@@ -870,7 +857,7 @@ CUDADevice::CUDAMem *CUDADevice::generic_alloc(device_memory &mem, size_t pitch_
if (mem_alloc_result != CUDA_SUCCESS) {
status = " failed, out of device and host memory";
- cuda_assert(mem_alloc_result);
+ set_error("System is out of GPU and shared host memory");
}
if (mem.name) {
@@ -2458,14 +2445,10 @@ void CUDADevice::task_cancel()
# define cuda_assert(stmt) \
{ \
CUresult result = stmt; \
-\
if (result != CUDA_SUCCESS) { \
- string message = string_printf("CUDA error: %s in %s", cuewErrorString(result), #stmt); \
- if (device->error_msg == "") \
- device->error_msg = message; \
- fprintf(stderr, "%s\n", message.c_str()); \
- /*cuda_abort();*/ \
- device->cuda_error_documentation(); \
+ const char *name = cuewErrorString(result); \
+ device->set_error( \
+ string_printf("%s in %s (device_cuda_impl.cpp:%d)", name, #stmt, __LINE__)); \
} \
} \
(void)0
@@ -2647,14 +2630,15 @@ bool CUDASplitKernel::enqueue_split_kernel_data_init(const KernelDimensions &dim
SplitKernelFunction *CUDASplitKernel::get_split_kernel_function(const string &kernel_name,
const DeviceRequestedFeatures &)
{
- CUDAContextScope scope(device);
- CUfunction func;
+ const CUDAContextScope scope(device);
- cuda_assert(
- cuModuleGetFunction(&func, device->cuModule, (string("kernel_cuda_") + kernel_name).data()));
- if (device->have_error()) {
- device->cuda_error_message(
- string_printf("kernel \"kernel_cuda_%s\" not
@@ Diff output truncated at 10240 characters. @@
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