기본 설치 위치는 아래와 같이 각양각색이다.
| VS2008 + cuda5.5 프로젝트 생성 (0) | 2014.01.13 |
|---|---|
| nvidia ion + ubuntu 12.04 LTS + cuda5.5 (0) | 2014.01.08 |
| cuda / cpu 테스트 드라이브 (0) | 2014.01.06 |
| cuda on ubuntu 12.04 LTS (0) | 2014.01.06 |
| cuda 5.5 (0) | 2014.01.06 |
| nvidia ion + ubuntu 12.04 LTS + cuda5.5 (0) | 2014.01.08 |
|---|---|
| cuda on windows 7 (0) | 2014.01.06 |
| cuda on ubuntu 12.04 LTS (0) | 2014.01.06 |
| cuda 5.5 (0) | 2014.01.06 |
| CUDA Capability별 기능차이 (0) | 2013.02.17 |
| Install the CUDA 5.5 Toolkit? ((y)es/(n)o/(q)uit): n
Install the CUDA 5.5 Samples? ((y)es/(n)o/(q)uit): y
Enter CUDA Samples Location [ default is /home/minimonk/NVIDIA_CUDA-5.5_Samples ]:
Enter Toolkit Location [ default is /usr/local/cuda-5.5 ]: |
| $ sudo apt-cache search cuda
boinc-nvidia-cuda - metapackage for CUDA-savvy BOINC client and manager
libthrust-dev - Thrust - C++ template library for CUDA
pyrit - GPGPU-driven WPA/WPA2-PSK key cracker
python-pytools - big bag of things supplementing Python standard library
suricata - Next Generation Intrusion Detection and Prevention Tool
libcublas4 - NVIDIA CUDA BLAS runtime library
libcudart4 - NVIDIA CUDA runtime library
libcufft4 - NVIDIA CUDA FFT runtime library
libcurand4 - NVIDIA CUDA Random Numbers Generation runtime library
libcusparse4 - NVIDIA CUDA Sparse Matrix runtime library
libnpp4 - NVIDIA Performance Primitives runtime library
nvidia-compute-profiler - NVIDIA Compute Visual Profiler
nvidia-cuda-dev - NVIDIA CUDA development files
nvidia-cuda-doc - NVIDIA CUDA and OpenCL documentation
nvidia-cuda-gdb - NVIDIA CUDA GDB
nvidia-cuda-toolkit - NVIDIA CUDA toolkit
nvidia-304 - NVIDIA binary Xorg driver, kernel module and VDPAU library
nvidia-304-updates - NVIDIA binary Xorg driver, kernel module and VDPAU library
nvidia-319 - NVIDIA binary Xorg driver, kernel module and VDPAU library
nvidia-319-updates - NVIDIA binary Xorg driver, kernel module and VDPAU library
python-pycuda - Python module to access Nvidia‘s CUDA parallel computation API
python-pycuda-doc - module to access Nvidia‘s CUDA parallel computation API (documentation)
python-pycuda-headers - headers for Python module to access Nvidia‘s CUDA parallel computation API
cuda-repo-ubuntu1204 - CUDA repo configuration files. |
| $ sudo apt-get install nvidia-cuda-dev nvidia-cuda-doc
패키지 목록을 읽는 중입니다... 완료
의존성 트리를 만드는 중입니다
상태 정보를 읽는 중입니다... 완료
다음 패키지를 더 설치할 것입니다:
cpp-4.4 g++-4.4 gcc-4.4 gcc-4.4-base libcublas4 libcudart4 libcufft4 libcurand4 libcusparse4
libnpp4 libqtassistantclient4 libstdc++6-4.4-dev libthrust-dev libvdpau-dev
nvidia-compute-profiler nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-opencl-dev opencl-headers
제안하는 패키지:
gcc-4.4-locales g++-4.4-multilib gcc-4.4-doc libstdc++6-4.4-dbg gcc-4.4-multilib
libmudflap0-4.4-dev libgcc1-dbg libgomp1-dbg libmudflap0-dbg libcloog-ppl0 libppl-c2 libppl7
libstdc++6-4.4-doc libvdpau-doc
다음 새 패키지를 설치할 것입니다:
cpp-4.4 g++-4.4 gcc-4.4 gcc-4.4-base libcublas4 libcudart4 libcufft4 libcurand4 libcusparse4
libnpp4 libqtassistantclient4 libstdc++6-4.4-dev libthrust-dev libvdpau-dev
nvidia-compute-profiler nvidia-cuda-dev nvidia-cuda-doc nvidia-cuda-gdb nvidia-cuda-toolkit
nvidia-opencl-dev opencl-headers
0개 업그레이드, 21개 새로 설치, 0개 제거 및 4개 업그레이드 안 함.
142 M바이트 아카이브를 받아야 합니다.
이 작업 후 467 M바이트의 디스크 공간을 더 사용하게 됩니다.
계속 하시겠습니까 [Y/n]? |
| $ sudo ./cuda_5.5.22_linux_32.run
NVIDIA CUDA General Terms
-------------------------
The Software may collect non-personally identifiable
information for the purposes of customizing information
delivered to you and improving future versions of the
Software. Such information, including IP address and system
configuration, will only be collected on an anonymous basis
and cannot be linked to any personally identifiable
information. Personally identifiable information such as your
username or hostname is not collected.
-------------------------------------------------------------
Do you accept the previously read EULA? (accept/decline/quit): accept
Install NVIDIA Accelerated Graphics Driver for Linux-x86 319.37? ((y)es/(n)o/(q)uit): y
Install the CUDA 5.5 Toolkit? ((y)es/(n)o/(q)uit): y
Enter Toolkit Location [ default is /usr/local/cuda-5.5 ]:
Install the CUDA 5.5 Samples? ((y)es/(n)o/(q)uit): y
Enter CUDA Samples Location [ default is /home/minimonk/NVIDIA_CUDA-5.5_Samples ]:
Installing the NVIDIA display driver...
Installing the CUDA Toolkit in /usr/local/cuda-5.5 ...
Installing the CUDA Samples in /home/minimonk/NVIDIA_CUDA-5.5_Samples ...
Copying samples to /home/minimonk/NVIDIA_CUDA-5.5_Samples/NVIDIA_CUDA-5.5_Samples now...
Finished copying samples.
===========
= Summary =
===========
Driver: Installed
Toolkit: Installed in /usr/local/cuda-5.5
Samples: Installed in /home/minimonk/NVIDIA_CUDA-5.5_Samples
* Please make sure your PATH includes /usr/local/cuda-5.5/bin
* Please make sure your LD_LIBRARY_PATH
* for 32-bit Linux distributions includes /usr/local/cuda-5.5/lib
* for 64-bit Linux distributions includes /usr/local/cuda-5.5/lib64:/lib
* OR
* for 32-bit Linux distributions add /usr/local/cuda-5.5/lib
* for 64-bit Linux distributions add /usr/local/cuda-5.5/lib64 and /lib
* to /etc/ld.so.conf and run ldconfig as root
* To uninstall CUDA, remove the CUDA files in /usr/local/cuda-5.5
* Installation Complete
Please see CUDA_Getting_Started_Linux.pdf in /usr/local/cuda-5.5/doc/pdf for detailed information on setting up CUDA.
Logfile is /tmp/cuda_install_5918.log
|
| cuda on windows 7 (0) | 2014.01.06 |
|---|---|
| cuda / cpu 테스트 드라이브 (0) | 2014.01.06 |
| cuda 5.5 (0) | 2014.01.06 |
| CUDA Capability별 기능차이 (0) | 2013.02.17 |
| Nvidia GTX 시리즈별 코드네임 (0) | 2013.02.17 |
| cuda / cpu 테스트 드라이브 (0) | 2014.01.06 |
|---|---|
| cuda on ubuntu 12.04 LTS (0) | 2014.01.06 |
| CUDA Capability별 기능차이 (0) | 2013.02.17 |
| Nvidia GTX 시리즈별 코드네임 (0) | 2013.02.17 |
| cuda deviceQuery on GTX650 (0) | 2013.02.17 |
| #define NDEBUG // disable assert() calls |
#include <assert.h> void assert(scalar expression);[링크 : http://linux.die.net/man/3/assert] |
| $ gcc c.c
/tmp/ccpSwySM.o: In function `main':
c.c:(.text+0x11): undefined reference to `assert'
collect2: ld returned 1 exit status |
#include "stdio.h"
#include "assert.h"
int main()
{
assert(0);
return 0;
}| $ gcc c.c
/tmp/ccpSwySM.o: In function `main':
c.c:(.text+0x11): undefined reference to `assert'
collect2: ld returned 1 exit status |
| typeof (0) | 2014.03.11 |
|---|---|
| const / pointer (0) | 2014.02.25 |
| printf의 %s와 %S (0) | 2013.06.15 |
| win32api - joystick 예제 (0) | 2013.06.15 |
| Windows IME (0) | 2013.02.14 |
| 우분투에서 openGL 시작하기 (0) | 2015.07.20 |
|---|---|
| GL2PS : an OpenGL to PostScript printing library (0) | 2014.03.06 |
| openGL에서 AVI 동영상 재생하기 (0) | 2013.04.09 |
| openGL gcc에서 컴파일 하기 (0) | 2012.06.02 |
| glsl과 glew의 연관관계 (0) | 2011.11.22 |
| int a;
#pragma omp parallel for
for(a = 0; a < 100; a++)
printf("%d",a); |
| int a;
#pragma omp parallel for private(a)
for(a = 0; a < 100; a++)
printf("%d",a); |
| openCV + openMP (0) | 2015.09.30 |
|---|---|
| openMP affinity 관련.. (0) | 2015.07.23 |
| openMP private copyin copyprivate firstprivate lastprivate (0) | 2013.11.28 |
| openMP reduction 절 (0) | 2013.11.28 |
| openMP atomic과 critical (0) | 2013.11.26 |
int _tmain(int argc, _TCHAR* argv[])
{
004113A0 push ebp
004113A1 mov ebp,esp
004113A3 sub esp,0CCh
004113A9 push ebx
004113AA push esi
004113AB push edi
004113AC lea edi,[ebp-0CCh]
004113B2 mov ecx,33h
004113B7 mov eax,0CCCCCCCCh
004113BC rep stos dword ptr es:[edi]
int a = 0;
004113BE mov dword ptr [a],0
a++;
004113C5 mov eax,dword ptr [a]
004113C8 add eax,1
004113CB mov dword ptr [a],eax
printf("hello world %d\n", a);
004113CE mov esi,esp
004113D0 mov eax,dword ptr [a]
004113D3 push eax
004113D4 push offset string "hello world %d\n" (41573Ch)
004113D9 call dword ptr [__imp__printf (4182BCh)]
004113DF add esp,8
004113E2 cmp esi,esp
004113E4 call @ILT+320(__RTC_CheckEsp) (411145h)
return 0;
004113E9 xor eax,eax
} |
| fasm / nasm / masm (0) | 2015.06.13 |
|---|---|
| 어셈블리 관련 (0) | 2015.06.11 |
| .DATA? 지시어 (0) | 2011.07.31 |
| x86 register (2) | 2011.07.17 |
| PowerPC(PPC) 어셈관련 내용 (0) | 2011.04.04 |
| openMP affinity 관련.. (0) | 2015.07.23 |
|---|---|
| openMP parallel for private (4) | 2013.12.12 |
| openMP reduction 절 (0) | 2013.11.28 |
| openMP atomic과 critical (0) | 2013.11.26 |
| openMP single 과 master의 차이점 (0) | 2013.11.26 |
$ cat test.c
#include "omp.h"
#define BUFFLEN 4096
#define NUMTHREAD 4
void thread()
{
int idx;
int arr[BUFFLEN];
int res = 0;
#pragma omp parallel
{
// initialize
#pragma omp for
for(idx = 0; idx < BUFFLEN; idx++)
arr[idx] = idx;
#pragma omp for reduction(+:res)
for(idx = 0; idx < BUFFLEN; idx++)
{
int tid = omp_get_thread_num();
res += arr[idx];
}
}
printf("res = %d\n",res);
}
int main(int argc, const char *argv[])
{
thread();
return 0;
}| openMP parallel for private (4) | 2013.12.12 |
|---|---|
| openMP private copyin copyprivate firstprivate lastprivate (0) | 2013.11.28 |
| openMP atomic과 critical (0) | 2013.11.26 |
| openMP single 과 master의 차이점 (0) | 2013.11.26 |
| openMP parallel default (0) | 2013.11.18 |
|
