-1

Somehow when I modify d_updated_water_flow_map in below code, d_terrain_height_map gets modified too / instead.

Changing the order of allocation for the two arrays fixes the problem, but I assume this is only masking the root-cause of the issue.

cudaCheck(cudaMalloc((void **)&d_water_flow_map, SIZE * 4)); 
cudaCheck(cudaMalloc((void **)&d_updated_water_flow_map, SIZE * 4)); // changing this array also changes d_terrain_height_map
cudaCheck(cudaMalloc((void **)&d_terrain_height_map, SIZE));

I am compiling kernel into a DLL and call it from below python file inside Blender 3D python interpreter. All of the values are 32 bit floats.

cu_include.h

#pragma once  

#ifdef MATHLIBRARY_EXPORTS  
#define MATHLIBRARY_API __declspec(dllexport)   
#else  
#define MATHLIBRARY_API __declspec(dllimport)   
#endif  


extern "C" __declspec(dllexport)
void init(float *t_height_map,
float *w_height_map,
float *s_height_map,
int SIZE_X,
int SIZE_Y);

extern "C" __declspec(dllexport)
void run_hydro_erosion(int cycles,
float t_step,
float min_tilt_angle,
float SEDIMENT_CAP,
float DISSOLVE_CONST,
float DEPOSIT_CONST,
int SIZE_X,
int SIZE_Y,
float PIPE_LENGTH,
float ADJACENT_LENGTH,
float TIME_STEP,
float MIN_TILT_ANGLE);

extern "C" __declspec(dllexport)
void free_mem();

extern "C" __declspec(dllexport)
void procedural_rain(float *water_height_map, float *rain_map, int SIZE_X, int SIZE_Y);

erosion_kernel.dll

#include "cu_include.h"

// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <time.h>
#include <iostream>
#include <algorithm>
#include <random>

// includes CUDA
#include <cuda_runtime.h>

using namespace std;

#define FLOW_RIGHT 0
#define FLOW_UP 1
#define FLOW_LEFT 2
#define FLOW_DOWN 3
#define X_VEL 0
#define Y_VEL 1
#define LEFT_CELL row, col - 1
#define RIGHT_CELL row, col + 1
#define ABOVE_CELL row - 1, col
#define BELOW_CELL row + 1, col

// CUDA API error checking macro
#define T 1024
#define M 1536
#define blockSize 1024
#define cudaCheck(error) \
  if (error != cudaSuccess) { \
    printf("Fatal error: %s at %s:%d\n", \
      cudaGetErrorString(error), \
      __FILE__, __LINE__); \
    exit(1); \
              }


__global__ void update_water_flow(float *water_height_map, float *water_flow_map, float *d_updated_water_flow_map, int SIZE_X, int SIZE_Y)
{
    int index = blockIdx.x * blockDim.x + threadIdx.x;
    int col = index % SIZE_X;
    int row = index / SIZE_X; 

    index = row * (SIZE_X * 4) + col * 4;   // 3D index
    d_updated_water_flow_map[index + FLOW_RIGHT] = 0;
    d_updated_water_flow_map[index + FLOW_UP] = 0;
    d_updated_water_flow_map[index + FLOW_LEFT] = 0;
    d_updated_water_flow_map[index + FLOW_DOWN] = 0;

}

static float *terrain_height_map;
static float *water_height_map;
static float *sediment_height_map;

void init(float *t_height_map,
    float *w_height_map,
    float *s_height_map,
    int SIZE_X,
    int SIZE_Y)
{
    /* set vars HOST*/
    terrain_height_map = t_height_map;
    water_height_map = w_height_map;
    sediment_height_map = s_height_map;
}

void run_hydro_erosion(int cycles,
    float t_step,
    float min_tilt_angle,
    float SEDIMENT_CAP,
    float DISSOLVE_CONST,
    float DEPOSIT_CONST,
    int SIZE_X,
    int SIZE_Y,
    float PIPE_LENGTH,
    float ADJACENT_LENGTH,
    float TIME_STEP,
    float MIN_TILT_ANGLE)
{ 
    int numBlocks = (SIZE_X * SIZE_Y + (blockSize - 1)) / blockSize;
    int SIZE = SIZE_X * SIZE_Y * sizeof(float);

    float *d_terrain_height_map, *d_updated_terrain_height_map;
    float *d_water_height_map, *d_updated_water_height_map;
    float *d_sediment_height_map, *d_updated_sediment_height_map;

    float *d_suspended_sediment_level;
    float *d_updated_suspended_sediment_level;
    float *d_water_flow_map;
    float *d_updated_water_flow_map;
    float *d_prev_water_height_map;
    float *d_water_velocity_vec;
    float *d_rain_map;

    cudaCheck(cudaMalloc(&d_water_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_updated_water_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_prev_water_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_water_flow_map, SIZE * 4));
    cudaCheck(cudaMalloc(&d_updated_water_flow_map, SIZE * 4)); // changing this array also changes d_terrain_height_map
    cudaCheck(cudaMalloc(&d_terrain_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_updated_terrain_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_sediment_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_updated_sediment_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_suspended_sediment_level, SIZE));
    cudaCheck(cudaMalloc(&d_updated_suspended_sediment_level, SIZE));
    cudaCheck(cudaMalloc(&d_rain_map, SIZE));
    cudaCheck(cudaMalloc(&d_water_velocity_vec, SIZE * 2));

    cudaCheck(cudaMemcpy(d_terrain_height_map, terrain_height_map, SIZE, cudaMemcpyHostToDevice));
    cudaCheck(cudaMemcpy(d_water_height_map, water_height_map, SIZE, cudaMemcpyHostToDevice));
    cudaCheck(cudaMemcpy(d_sediment_height_map, sediment_height_map, SIZE, cudaMemcpyHostToDevice));

    cout << "init terrain_height_map" << endl;
    for (int i = 0; i < SIZE_X * SIZE_Y; i++) {
        cout << terrain_height_map[i] << ", ";
        if (i % SIZE_X == 0 && i != 0) cout << endl;
    }

    /* launch the kernel on the GPU */
    float *temp;
    while (cycles--) {
        update_water_flow << < numBlocks, blockSize >> >(d_water_height_map, d_water_flow_map, d_updated_water_flow_map, SIZE_X, SIZE_Y); 
        temp = d_water_flow_map;
        d_water_flow_map = d_updated_water_flow_map;
        d_updated_water_flow_map = temp;        
    }
    cudaCheck(cudaMemcpy(terrain_height_map, d_terrain_height_map, SIZE, cudaMemcpyDeviceToHost)); 


    cout << "updated terrain" << endl;
    for (int i = 0; i < SIZE_X * SIZE_Y; i++) {
        cout << terrain_height_map[i] << ", ";
        if (i % SIZE_X == 0 && i != 0) cout << endl;
    } 
}

Python file

import bpy
import numpy
import ctypes
import random

width = 4
height = 4

size_x = width
size_y = height
N = size_x * size_y

scrpt_cycles = 1
kernel_cycles = 1
time_step = 0.005 
pipe_length = 1.0
adjacent_length = 1.0
min_tilt_angle = 10
sediment_cap = 0.01
dissolve_const = 0.01
deposit_const = 0.01

# initialize arrays
ter_height_map = numpy.ones((N), dtype=numpy.float32)
water_height_map = numpy.zeros((N), dtype=numpy.float32)
sed_height_map = numpy.zeros((N), dtype=numpy.float32)
rain_map = numpy.ones((N), dtype=numpy.float32)


# load terrain height from image
for i in range(0, len(ter_height_map)):
    ter_height_map[i] = 1


# import DLL
E = ctypes.cdll.LoadLibrary("E:/Programming/CUDA/erosion/Release/erosion_kernel.dll")

# initialize device memory
E.init( ctypes.c_void_p(ter_height_map.ctypes.data), 
        ctypes.c_void_p(water_height_map.ctypes.data),
        ctypes.c_void_p(sed_height_map.ctypes.data),
        ctypes.c_int(size_x),
        ctypes.c_int(size_y))


# run erosion
while(scrpt_cycles):
    scrpt_cycles = scrpt_cycles - 1  
    E.run_hydro_erosion(ctypes.c_int(kernel_cycles),
                        ctypes.c_float(time_step),
                        ctypes.c_float(min_tilt_angle), 
                        ctypes.c_float(sediment_cap), 
                        ctypes.c_float(dissolve_const), 
                        ctypes.c_float(deposit_const),
                        ctypes.c_int(size_x),
                        ctypes.c_int(size_y),
                        ctypes.c_float(pipe_length),
                        ctypes.c_float(adjacent_length),
                        ctypes.c_float(time_step),
                        ctypes.c_float(min_tilt_angle))

Wrong output:

enter image description here

Expected output (after I comment out update_water_flow):

//update_water_flow << < numBlocks, blockSize >> >(d_water_height_map, d_water_flow_map, d_updated_water_flow_map, SIZE_X, SIZE_Y);

enter image description here

Graphics card: GTX460M

Improve this question
12
  • Without an minimal reproducible example this question is s waste of everyone's time, including yours. Commented Aug 5, 2017 at 9:31
  • @talonmies I have added a working, minimal example! Sorry about that.. Commented Aug 5, 2017 at 13:21
  • 1
    This is illegal in CUDA: __device__ float *d_updated_water_flow_map; ... cudaCheck(cudaMalloc(&d_updated_water_flow_map, SIZE * 4)); and is a significant difference between the version of the code you have now posted compared to the version that was previously posted (which had d_updated_water_flow_map as an ordinary host stack variable). You cannot take the address of a __device__ variable in host code (even in a call/parameter for cudaMalloc) and this is not the right method to create a __device__ pointer variable. Commented Aug 5, 2017 at 13:46
  • @RobertCrovella I changed the code back to original design. I was trying something different and forgot to change the variables back to how they were originally. I tested and the issue is still happening. Modifying d_updated_water_flow_map still modifies d_terrain_height_map Commented Aug 5, 2017 at 13:54
  • run your code outside of blender with cuda-memcheck. I was able to do that just by removing import bpy from your python script and then running cuda-memcheck python test.py When I do that, cuda-memcheck reports invalid memory access errors in your kernel. Commented Aug 5, 2017 at 14:49

1 Answer 1

Reset to default
1

(Note that the code in this answer also gives a complete recipe/example for how to use CUDA code (e.g. CUDA device kernels) in a library that is shared with a python application using python ctypes. If you wish to use CUDA library functionality, the answer here provides an example, using python ctypes.)

The problem here is that the kernel was writing out-of-bounds, and apparently the compiler/runtime located the allocations close enough in device memory, that exceeding the bounds on the first allocation caused the code to write into the second allocation:

cudaCheck(cudaMalloc(&d_updated_water_flow_map, SIZE * 4)); // changing this array also changes d_terrain_height_map
cudaCheck(cudaMalloc(&d_terrain_height_map, SIZE));

The out-of-bounds accesses are coming about because the kernel launch involves more than enough threads (it is launching 1024 threads in this case) whereas we really only "need" SIZE_X*SIZE_Y threads (i.e. 16 in this example):

#define blockSize 1024
...
int numBlocks = (SIZE_X * SIZE_Y + (blockSize - 1)) / blockSize;
...
update_water_flow << < numBlocks, blockSize >> >(d_water_height_map, d_water_flow_map, d_updated_water_flow_map, SIZE_X, SIZE_Y);

This is of course "typical" in CUDA programming, to launch more than enough threads, but its important when doing this to include a "thread check" in the kernel, to prevent any "extra" threads from making any illegal, out-of-bounds accesses. In this case one possible kernel thread check might be like this:

if ((row >= SIZE_Y) || (col >= SIZE_X)) return;

Here's a fully-worked example based on the provided code (albeit on linux, and removing the blender dependency in the python code), showing the before-and-after effect. Note that we can run even a code like this with cuda-memcheck, which would have pointed out the out-of-bounds accesses in this case (omitted from the first example below, for clarity):

$ cat t383.cu
extern "C"
void init(float *t_height_map,
float *w_height_map,
float *s_height_map,
int SIZE_X,
int SIZE_Y);

extern "C"
void run_hydro_erosion(int cycles,
float t_step,
float min_tilt_angle,
float SEDIMENT_CAP,
float DISSOLVE_CONST,
float DEPOSIT_CONST,
int SIZE_X,
int SIZE_Y,
float PIPE_LENGTH,
float ADJACENT_LENGTH,
float TIME_STEP,
float MIN_TILT_ANGLE);

extern "C"
void free_mem();

extern "C"
void procedural_rain(float *water_height_map, float *rain_map, int SIZE_X, int SIZE_Y);

// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <time.h>
#include <iostream>
#include <algorithm>
#include <random>

// includes CUDA
#include <cuda_runtime.h>

using namespace std;

#define FLOW_RIGHT 0
#define FLOW_UP 1
#define FLOW_LEFT 2
#define FLOW_DOWN 3
#define X_VEL 0
#define Y_VEL 1
#define LEFT_CELL row, col - 1
#define RIGHT_CELL row, col + 1
#define ABOVE_CELL row - 1, col
#define BELOW_CELL row + 1, col

// CUDA API error checking macro
#define T 1024
#define M 1536
#define blockSize 1024
#define cudaCheck(error) \
  if (error != cudaSuccess) { \
    printf("Fatal error: %s at %s:%d\n", \
      cudaGetErrorString(error), \
      __FILE__, __LINE__); \
    exit(1); \
              }


__global__ void update_water_flow(float *water_height_map, float *water_flow_map, float *d_updated_water_flow_map, int SIZE_X, int SIZE_Y)
{
    int index = blockIdx.x * blockDim.x + threadIdx.x;
    int col = index % SIZE_X;
    int row = index / SIZE_X;

    index = row * (SIZE_X * 4) + col * 4;   // 3D index
#ifdef FIX
    if ((row >= SIZE_Y) || (col >= SIZE_X)) return;
#endif
    d_updated_water_flow_map[index + FLOW_RIGHT] = 0;
    d_updated_water_flow_map[index + FLOW_UP] = 0;
    d_updated_water_flow_map[index + FLOW_LEFT] = 0;
    d_updated_water_flow_map[index + FLOW_DOWN] = 0;

}

static float *terrain_height_map;
static float *water_height_map;
static float *sediment_height_map;

void init(float *t_height_map,
    float *w_height_map,
    float *s_height_map,
    int SIZE_X,
    int SIZE_Y)
{
    /* set vars HOST*/
    terrain_height_map = t_height_map;
    water_height_map = w_height_map;
    sediment_height_map = s_height_map;
}

void run_hydro_erosion(int cycles,
    float t_step,
    float min_tilt_angle,
    float SEDIMENT_CAP,
    float DISSOLVE_CONST,
    float DEPOSIT_CONST,
    int SIZE_X,
    int SIZE_Y,
    float PIPE_LENGTH,
    float ADJACENT_LENGTH,
    float TIME_STEP,
    float MIN_TILT_ANGLE)
{
    int numBlocks = (SIZE_X * SIZE_Y + (blockSize - 1)) / blockSize;
    int SIZE = SIZE_X * SIZE_Y * sizeof(float);

    float *d_terrain_height_map, *d_updated_terrain_height_map;
    float *d_water_height_map, *d_updated_water_height_map;
    float *d_sediment_height_map, *d_updated_sediment_height_map;

    float *d_suspended_sediment_level;
    float *d_updated_suspended_sediment_level;
    float *d_water_flow_map;
    float *d_updated_water_flow_map;
    float *d_prev_water_height_map;
    float *d_water_velocity_vec;
    float *d_rain_map;

    cudaCheck(cudaMalloc(&d_water_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_updated_water_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_prev_water_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_water_flow_map, SIZE * 4));
    cudaCheck(cudaMalloc(&d_updated_water_flow_map, SIZE * 4)); // changing this array also changes d_terrain_height_map
    cudaCheck(cudaMalloc(&d_terrain_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_updated_terrain_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_sediment_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_updated_sediment_height_map, SIZE));
    cudaCheck(cudaMalloc(&d_suspended_sediment_level, SIZE));
    cudaCheck(cudaMalloc(&d_updated_suspended_sediment_level, SIZE));
    cudaCheck(cudaMalloc(&d_rain_map, SIZE));
    cudaCheck(cudaMalloc(&d_water_velocity_vec, SIZE * 2));

    cudaCheck(cudaMemcpy(d_terrain_height_map, terrain_height_map, SIZE, cudaMemcpyHostToDevice));
    cudaCheck(cudaMemcpy(d_water_height_map, water_height_map, SIZE, cudaMemcpyHostToDevice));
    cudaCheck(cudaMemcpy(d_sediment_height_map, sediment_height_map, SIZE, cudaMemcpyHostToDevice));

    cout << "init terrain_height_map" << endl;
    for (int i = 0; i < SIZE_X * SIZE_Y; i++) {
        cout << terrain_height_map[i] << ", ";
        if (i % SIZE_X == 0 && i != 0) cout << endl;
    }

    /* launch the kernel on the GPU */
    float *temp;
    while (cycles--) {
        update_water_flow << < numBlocks, blockSize >> >(d_water_height_map, d_water_flow_map, d_updated_water_flow_map, SIZE_X, SIZE_Y);
        temp = d_water_flow_map;
        d_water_flow_map = d_updated_water_flow_map;
        d_updated_water_flow_map = temp;
    }
    cudaCheck(cudaMemcpy(terrain_height_map, d_terrain_height_map, SIZE, cudaMemcpyDeviceToHost));


    cout << "updated terrain" << endl;
    for (int i = 0; i < SIZE_X * SIZE_Y; i++) {
        cout << terrain_height_map[i] << ", ";
        if (i % SIZE_X == 0 && i != 0) cout << endl;
    }
}
$ cat t383.py
import numpy
import ctypes
import random

width = 4
height = 4

size_x = width
size_y = height
N = size_x * size_y

scrpt_cycles = 1
kernel_cycles = 1
time_step = 0.005
pipe_length = 1.0
adjacent_length = 1.0
min_tilt_angle = 10
sediment_cap = 0.01
dissolve_const = 0.01
deposit_const = 0.01

# initialize arrays
ter_height_map = numpy.ones((N), dtype=numpy.float32)
water_height_map = numpy.zeros((N), dtype=numpy.float32)
sed_height_map = numpy.zeros((N), dtype=numpy.float32)
rain_map = numpy.ones((N), dtype=numpy.float32)


# load terrain height from image
for i in range(0, len(ter_height_map)):
    ter_height_map[i] = 1


# import DLL
E = ctypes.cdll.LoadLibrary("./t383.so")

# initialize device memory
E.init( ctypes.c_void_p(ter_height_map.ctypes.data),
        ctypes.c_void_p(water_height_map.ctypes.data),
        ctypes.c_void_p(sed_height_map.ctypes.data),
        ctypes.c_int(size_x),
        ctypes.c_int(size_y))


# run erosion
while(scrpt_cycles):
    scrpt_cycles = scrpt_cycles - 1
    E.run_hydro_erosion(ctypes.c_int(kernel_cycles),
                        ctypes.c_float(time_step),
                        ctypes.c_float(min_tilt_angle),
                        ctypes.c_float(sediment_cap),
                        ctypes.c_float(dissolve_const),
                        ctypes.c_float(deposit_const),
                        ctypes.c_int(size_x),
                        ctypes.c_int(size_y),
                        ctypes.c_float(pipe_length),
                        ctypes.c_float(adjacent_length),
                        ctypes.c_float(time_step),
                        ctypes.c_float(min_tilt_angle))
$ nvcc -Xcompiler -fPIC -std=c++11 -shared -arch=sm_61 -o t383.so t383.cu
$ python t383.py
init terrain_height_map
1, 1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, updated terrain
0, 0, 0, 0, 0,
0, 0, 0, 0,
0, 0, 0, 0,
0, 0, 0, 
$ nvcc -Xcompiler -fPIC -std=c++11 -shared -arch=sm_61 -o t383.so t383.cu -DFIX
$ cuda-memcheck python t383.py
========= CUDA-MEMCHECK
init terrain_height_map
1, 1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, updated terrain
1, 1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 
========= ERROR SUMMARY: 0 errors
$

If we compile the previous example without the fix, but run it with cuda-memcheck we will get output indicating the out-of-bounds accesses:

$nvcc -Xcompiler -fPIC -std=c++11 -shared -arch=sm_61 -o t383.so t383.cu
$ cuda-memcheck python t383.py
========= CUDA-MEMCHECK
init terrain_height_map
1, 1, 1, 1, 1,
1, 1, 1, 1,
1, 1, 1, 1,
========= Invalid __global__ write of size 4
=========     at 0x000002f0 in update_water_flow(float*, float*, float*, int, int)
=========     by thread (31,0,0) in block (0,0,0)
=========     Address 0x1050d6009f0 is out of bounds
=========     Saved host backtrace up to driver entry point at kernel launch time
=========     Host Frame:/usr/lib/x86_64-linux-gnu/libcuda.so.1 (cuLaunchKernel + 0x2c5) [0x204505]
=========     Host Frame:./t383.so [0x1c291]
=========     Host Frame:./t383.so [0x39e33]
=========     Host Frame:./t383.so [0x6879]
=========     Host Frame:./t383.so (_Z43__device_stub__Z17update_water_flowPfS_S_iiPfS_S_ii + 0xe3) [0x6747]
=========     Host Frame:./t383.so (_Z17update_water_flowPfS_S_ii + 0x38) [0x6781]
=========     Host Frame:./t383.so (run_hydro_erosion + 0x8f2) [0x648b]
=========     Host Frame:/usr/lib/x86_64-linux-gnu/libffi.so.6 (ffi_call_unix64 + 0x4c) [0x5adc]
=========     Host Frame:/usr/lib/x86_64-linux-gnu/libffi.so.6 (ffi_call + 0x1fc) [0x540c]
=========     Host Frame:/usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so (_ctypes_callproc + 0x48e) [0x145fe]
=========     Host Frame:/usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so [0x15f9e]
=========     Host Frame:python (PyEval_EvalFrameEx + 0x98d) [0x1244dd]
=========     Host Frame:python [0x167d14]
=========     Host Frame:python (PyRun_FileExFlags + 0x92) [0x65bf4]
=========     Host Frame:python (PyRun_SimpleFileExFlags + 0x2ee) [0x6612d]
=========     Host Frame:python (Py_Main + 0xb5e) [0x66d92]
=========     Host Frame:/lib/x86_64-linux-gnu/libc.so.6 (__libc_start_main + 0xf5) [0x21f45]
=========     Host Frame:python [0x177c2e]
=========
========= Invalid __global__ write of size 4
=========     at 0x000002f0 in update_water_flow(float*, float*, float*, int, int)
=========     by thread (30,0,0) in block (0,0,0)
=========     Address 0x1050d6009e0 is out of bounds
=========     Saved host backtrace up to driver entry point at kernel launch time
=========     Host Frame:/usr/lib/x86_64-linux-gnu/libcuda.so.1 (cuLaunchKernel + 0x2c5) [0x204505]
=========     Host Frame:./t383.so [0x1c291]
=========     Host Frame:./t383.so [0x39e33]
=========     Host Frame:./t383.so [0x6879]
=========     Host Frame:./t383.so (_Z43__device_stub__Z17update_water_flowPfS_S_iiPfS_S_ii + 0xe3) [0x6747]
=========     Host Frame:./t383.so (_Z17update_water_flowPfS_S_ii + 0x38) [0x6781]
=========     Host Frame:./t383.so (run_hydro_erosion + 0x8f2) [0x648b]
=========     Host Frame:/usr/lib/x86_64-linux-gnu/libffi.so.6 (ffi_call_unix64 + 0x4c) [0x5adc]
=========     Host Frame:/usr/lib/x86_64-linux-gnu/libffi.so.6 (ffi_call + 0x1fc) [0x540c]
=========     Host Frame:/usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so (_ctypes_callproc + 0x48e) [0x145fe]
=========     Host Frame:/usr/lib/python2.7/lib-dynload/_ctypes.x86_64-linux-gnu.so [0x15f9e]
=========     Host Frame:python (PyEval_EvalFrameEx + 0x98d) [0x1244dd]
=========     Host Frame:python [0x167d14]
=========     Host Frame:python (PyRun_FileExFlags + 0x92) [0x65bf4]
=========     Host Frame:python (PyRun_SimpleFileExFlags + 0x2ee) [0x6612d]
=========     Host Frame:python (Py_Main + 0xb5e) [0x66d92]
=========     Host Frame:/lib/x86_64-linux-gnu/libc.so.6 (__libc_start_main + 0xf5) [0x21f45]
=========     Host Frame:python [0x177c2e]
=========
... (output truncated for brevity of presentation)
========= ERROR SUMMARY: 18 errors
$
Improve this answer
Sign up to request clarification or add additional context in comments.

10 Comments

Thanks a lot again! Btw, I tried running cuda-memcheck I get the following two errors:========= Internal Memcheck Error: Device not supported and ========= Internal Memcheck Error: Initialization failed
which CUDA version, which driver version, and which GPU? You may be running a version of cuda-memcheck which is too old for your GPU or does not match the installed CUDA version.
GeForce GTX 460M, driver: 384.76, not sure which CUDA version, does this help: link
The CUDA version matters. What do you get if you type cuda-memcheck --version
CUDA-MEMCHECK version 8.0.61 ID:(41)
|

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.