multi-gpu

CUDA fails when trying to use both onboard iGPU and Nvidia discrete card. How can i use both discrete nvidia and integrated (onboard) intel gpu? [closed]

由 ぃ、小莉子 提交于 2019-11-28 06:56:05
问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . I had recently some trouble making my pc (ivybridge) use the onboard gpu (intel igpu HD4000) for normal screen display usage, while i run my CUDA programs for computations on the discrete Nvidia GT 640 i have on my machine. The problem was that under iGPU display, CUDA would be unable to spot the nvidia card ,

multi-GPU basic usage

由 走远了吗. 提交于 2019-11-27 07:00:06
How can I use two devices in order to improve for example the performance of the following code (sum of vectors)? Is it possible to use more devices "at the same time"? If yes, how can I manage the allocations of the vectors on the global memory of the different devices? #include <stdio.h> #include <stdlib.h> #include <math.h> #include <time.h> #include <cuda.h> #define NB 32 #define NT 500 #define N NB*NT __global__ void add( double *a, double *b, double *c); //=========================================== __global__ void add( double *a, double *b, double *c){ int tid = threadIdx.x + blockIdx.x

multi-GPU basic usage

由 人走茶凉 提交于 2019-11-26 12:59:45
问题 How can I use two devices in order to improve for example the performance of the following code (sum of vectors)? Is it possible to use more devices \"at the same time\"? If yes, how can I manage the allocations of the vectors on the global memory of the different devices? #include <stdio.h> #include <stdlib.h> #include <math.h> #include <time.h> #include <cuda.h> #define NB 32 #define NT 500 #define N NB*NT __global__ void add( double *a, double *b, double *c); //============================

Using Java with Nvidia GPU&#39;s (cuda)

由 女生的网名这么多〃 提交于 2019-11-26 02:03:29
问题 I\'m working on a business project that is done in java and needs huge computation power to compute business markets. Simple math but with huge amount of data. We ordered some cuda gpu\'s to try it with and since Java is not supported by cuda, Im wondering where to start. Should I build a JNI interface? Should I use JCUDA or is there other ways? I dont have experience in this field and I would like if someone could direct me to something so I can start researching and learning. 回答1: First of
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