Recently, I learnt how to code using the cuda unified memory. But what weird is that the kernel reports different result when I replace the pointer object by the non-pointer one.
Please refer to the Core.cuh and main.cu.
The ClassManaged.h is base class for new and delete overload and CMakeList.txt for build the test case.
//ClassManaged.h This file overloads the new and delete operator for children class
#ifndef __CLASS_MANAGED_H__
#define __CLASS_MANAGED_H__
#include <cuda_runtime_api.h>
class Managed
{
public:
void *operator new(size_t len)
{
printf("-->Managed call!\n");
void *ptr;
cudaMallocManaged(&ptr, len);
cudaDeviceSynchronize();
printf(" Address for Managed constructor: %p\n", ptr);
return ptr;
}
void operator delete(void *ptr)
{
cudaDeviceSynchronize();
cudaFree(ptr);
}
void* operator new[] (size_t len)
{
void *ptr;
cudaMallocManaged(&ptr, len);
cudaDeviceSynchronize();
return ptr;
}
void operator delete[] (void* ptr)
{
cudaDeviceSynchronize();
cudaFree(ptr);
}
};
#endif
//Core.cuh where the bug appears
#ifndef __CORE_CUH__
#define __CORE_CUH__
#include "ClassManaged.h"
#include "cuda_runtime.h"
#include <string>
#include "stdio.h"
class Box : public Managed{
public:
int a;
int b;
};
class Core : public Managed{
public:
__host__ __device__ Core(int cnumin)
{
c_num = cnumin;
}
__host__ __device__ ~Core()
{
cudaFree(datan);
}
void initialize()
{
cudaMallocManaged((void**)&datan, offset*c_num*sizeof(int));
//cudaMallocManaged((void**)&box, sizeof(Box)); // Test case 1 pointer object
//box = new Box(); // Test case 1 pointer object
}
public:
//Box* box; // Test Case 1: pointer object (Everything is ok!)
Box box; // Test Case 2: non-pointer object (with BUG)
int* datan;
public:
int m_id = 0;
int c_num;
int support_num = 0;
const int offset = 12;
float delta = 1.2;
};
// A minimal version for kernel
__global__ void WorkFlow_kernel_forcore(Core* core)
{
volatile int coreno = blockIdx.x;
if(threadIdx.x == 0)
{
printf("\n--->Kernel data!\n");
printf(" Core address in kernel: %p\n", core);
printf(" Box address in kernel: %p\n", &(core->box));
//printf(" Box address in kernel: %p\n", core->box);
printf("\n Addr m_id: %p\n", &(core->m_id));
printf(" Addr c_num: %p\n", &(core->c_num));
printf(" Addr support_num: %p\n", &(core->support_num));
printf(" Addr Offset: %p\n", &(core->offset));
printf(" Addr Delta: %p\n", &(core->delta));
printf("\n Val m_id: %d\n", core->m_id);
printf(" Val c_num: %d\n", core->c_num);
printf(" Val support_num: %d\n", core->support_num);
printf(" Val Offset: %d\n", core->offset);
printf(" Val Delta: %.5f\n", core->delta);
}
// The kernel outputs the wrong result for non-pointer Core::box.
}
//main.cu
#include <cuda_runtime.h>
#include "Core.cuh"
int main()
{
// 1 Only Core involved
// This is a minimal version suggested by Sebastian (only Core and kernel existed here)
Core* core = new Core(20); // Here, the Core still inherits from Managed. Because it seems more convenient to execute constructor on device with help of new and delete overload.
core->initialize();
printf(" Double check core address: %p\n", core);
printf(" Double check box address: %p\n", &(core->box));
//printf(" Double check box address: %p\n", core->box);
printf("\n Double check Addr m_id: %p\n", &(core->m_id));
printf(" Double check Addr c_num: %p\n", &(core->c_num));
printf(" Double check Addr support_num: %p\n", &(core->support_num));
printf(" Double check Addr Offset: %p\n", &(core->offset));
printf(" Double check Addr Delta: %p\n", &(core->delta));
WorkFlow_kernel_forcore<<<1,1>>>(core); // The output is the wrong result when non-pointer Core::box defined!
delete core;
// ----------------------------------Wrong result address output
// -->Managed call!
// Address for Managed constructor: 0000000A00000000
// Double check core address: 0000000A00000000
// Double check box address: 0000000000000000
// Double check Addr m_id: 0000000A00000010
// Double check Addr c_num: 0000000A00000014
// Double check Addr support_num: 0000000A00000018
// Double check Addr Offset: 0000000A0000001C
// Double check Addr Delta: 0000000A00000020
// --->Kernel data!
// Core address in kernel: 0000000A00000000
// Box address in kernel: 0000000A00000004
// Addr m_id: 0000000A00000018
// Addr c_num: 0000000A0000001C
// Addr support_num: 0000000A00000020
// Addr Offset: 0000000A00000024
// Addr Delta: 0000000A00000028
// Val m_id: 0
// Val c_num: 12
// Val support_num: 1067030938
// Val Offset: 0
// Val Delta: 0.00000
// ----------------------------------Correct result address output
// -->Managed call!
// Address for Managed constructor: 0000000A00000000
// -->Managed call!
// Address for Managed constructor: 0000000A00030000
// Double check core address: 0000000A00000000
// Double check box address: 0000000A00030000
// Double check Addr m_id: 0000000A00000010
// Double check Addr c_num: 0000000A00000014
// Double check Addr support_num: 0000000A00000018
// Double check Addr Offset: 0000000A0000001C
// Double check Addr Delta: 0000000A00000020
// --->Kernel data!
// Core address in kernel: 0000000A00000000
// Box address in kernel: 0000000A00030000
// Addr m_id: 0000000A00000010
// Addr c_num: 0000000A00000014
// Addr support_num: 0000000A00000018
// Addr Offset: 0000000A0000001C
// Addr Delta: 0000000A00000020
// Val m_id: 0
// Val c_num: 20
// Val support_num: 0
// Val Offset: 12
// Val Delta: 1.20000
// 2 This version replace the unified memory of core by cudaMalloc and cudaMemcpy.
// NOTE: Before run the test 2, please comment the (cancel the inheritance from Managed)
// class Core /*: public Managed*/ {
//Core* host_core = new Core(20);
//Core* device_core;
//cudaMalloc(&device_core, sizeof(Core));
//cudaMemcpy(device_core, host_core, sizeof(Core), cudaMemcpyHostToDevice);
//WorkFlow_kernel_forcore<<<1,1>>>(device_core);
// !!!---> This kernel output the correct information: 0, 20, 0, 12, 1.2
//delete host_core;
//cudaFree(device_core);
return 0;
}
//CMakeList.txt
project (gputask CXX CUDA)
CMAKE_MINIMUM_REQUIRED(VERSION 3.10 FATAL_ERROR)
if (MSVC)
set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS ON)
endif (MSVC)
if(CMAKE_INSTALL_PREFIX_INITIALIZED_TO_DEFAULT)
set(CMAKE_INSTALL_PREFIX "${CMAKE_SOURCE_DIR}/gputask" CACHE PATH "This is default path" FORCE)
endif()
SET(CMAKE_SKIP_BUILD_RPATH FALSE)
SET(CMAKE_BUILD_WITH_INSTALL_RPATH FALSE)
SET(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE)
option(ENABLE_EMBED_CUDA "Enable embedding of the CUDA libraries into lib" OFF)
set(GPUTASK_NVCC_ARCHS_DEFAULT "")
list(APPEND GPUTASK_NVCC_ARCHS_DEFAULT 75)
set(GPUTASK_NVCC_ARCHS ${GPUTASK_NVCC_ARCHS_DEFAULT} CACHE STRING "The SM architectures to build code for.")
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -Xcudafe --diag_suppress=code_is_unreachable")
if(NOT CMAKE_BUILD_TYPE AND NOT CMAKE_CONFIGURATION_TYPES)
message(STATUS "Setting build type to 'Release' as none was specified.")
set(CMAKE_BUILD_TYPE Release CACHE STRING "Choose the type of build." FORCE)
set_property(CACHE CMAKE_BUILD_TYPE PROPERTY STRINGS "Debug" "Release"
"MinSizeRel" "RelWithDebInfo")
endif()
set(CMAKE_CXX_STANDARD 14)
SET(CMAKE_CUDA_STANDARD 14)
set(CMAKE_CXX_STANDARD_REQUIRED ON)
if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wall -Wno-unknown-pragmas -Wno-deprecated-declarations -DMPM_CODE")
set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -Wall -Wno-unknown-pragmas")
endif()
set(CUDA_ARCH_LIST 70 75 CACHE STRING "List of target sm_ architectures to compile CUDA code for. Separate with semicolons.")
foreach(_cuda_arch ${CUDA_ARCH_LIST})
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -gencode=arch=compute_${_cuda_arch},code=sm_${_cuda_arch}")
endforeach (_cuda_arch)
if (ENABLE_EMBED_CUDA)
get_filename_component(_cuda_libdir ${CUDA_CUDART_LIBRARY} PATH)
FILE(GLOB _cuda_libs ${_cuda_libdir}/libcurand.* ${_cuda_libdir}/libcufft.* ${_cuda_libdir}/libcusolver.* ${_cuda_libdir}/libcusparse.*)
install(PROGRAMS ${_cuda_libs} DESTINATION ${CMAKE_INSTALL_PREFIX}/lib)
endif ()
set(GPUTASK_COMMON_LIBS ${ADDITIONAL_LIBS})
list(APPEND GPUTASK_COMMON_LIBS ${CUDA_LIBRARIES} ${CUDA_cufft_LIBRARY} ${CUDA_curand_LIBRARY})
if (ENABLE_NVTOOLS)
list(APPEND GPUTASK_COMMON_LIBS ${CUDA_nvToolsExt_LIBRARY})
endif()
include_directories(${CUDA_INCLUDE})
exec_program("date +%x" OUTPUT_VARIABLE COMPILE_DATE)
set(CUDA_VERBOSE_BUILD on)
set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -DNVCC -ftz=true")
set(GPUTASK_ROOT "${CMAKE_SOURCE_DIR}")
ADD_EXECUTABLE(mytask ${CMAKE_CURRENT_SOURCE_DIR}/main.cu)
INSTALL(TARGETS mytask DESTINATION ${CMAKE_INSTALL_PREFIX}/bin)
Kernel prints different information for class Core between the non-pointer or pointer see the printf code block.
Platform information:
OS: Win 10
Cuda: 11.1.74 ship with RTX 2060
Win SDK 10.0.18362.0
MSVC 19.28.29334.0
Visual Studio 16 2019
In brief, it seems that the wrong output in test1 of main.cu results from the class Core : public Managed (overload unified memory new and delete).
The new revised code print the address for address of all the members of Core at the stage of cudaMallocManaged and kernel.
It is clear that the address of box differs in BUG version while kernel is called (say box address jumps from 0 to 4).
There is no such thing in the correct version. It may be deduced that the box address flows from somewhere to somewhere?
Does it mean that memory out of range or leak? (I guess but not sure about it).
SOLVED------------------------->!!!!
Thanks to Robert, I find the reason of this bug. Please refer to NVIDIA DOC.
The CUDA compiler follows the IA64 ABI for class layout, while the Microsoft host compiler does not. Let T denote a pointer to member type, or a class type that satisfies any of the following conditions:
T has virtual functions.
T has a virtual base class.
T has multiple inheritance with more than one direct or indirect empty base class.
All direct and indirect base classes B of T are empty and the type of the first field F of T uses B in its definition, such that B is laid out at offset 0 in the definition of F.
Since both box and Core are children of Managed, if we place the box at the first order, the code matches the fourth case，All direct and indirect base classes B of T are empty...
And undefined behaviour on Win OS can appear due to the IA64 ABI for cuda compared to x64 ABI (Win host).
I greatly appreciate your suggestions! Thank you very much!
