The code is written for my rtx 4070s so there is no guarantee it will work on others gpus
but it probably will work on every rtx 4000, i will take a closer look at portability in the future
you can select your architecture passing the -DCMAKE_CUDA_ARCHITECTURES=XX flag where XX
is your cuda architecture.
| GPU Series | Compute Capability |
|---|---|
| RTX 40xx (Ada) | 89 |
| RTX 30xx (Ampere) | 86 |
| RTX 20xx (Turing) | 75 |
| GTX 16xx (Turing) | 75 |
| GTX 10xx (Pascal) | 61, 62 |
| GTX 900 (Maxwell) | 50, 52 |
otherwise you can use nvcc -ls-arch to get a detailed list
mkdir -p build && cd build
cmake \
-DCMAKE_BUILD_TYPE=Release \
-DCMAKE_CUDA_ARCHITECTURES=89 \
..
make -j`nproc --all`
./cuda
feh test.ppmLearning resources
- https://en.wikipedia.org/wiki/Netpbm
- https://developer.nvidia.com/blog/cuda-pro-tip-write-flexible-kernels-grid-stride-loops/
- https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#thread-hierarchy
- https://codingbyexample.com/2018/12/17/cuda-threads-memory/
- https://www.youtube.com/playlist?list=PLC6u37oFvF40BAm7gwVP7uDdzmW83yHPe
- https://cuda-tutorial.readthedocs.io/en/latest/
- https://tschmidt23.github.io/cse599i/CSE%20599%20I%20Accelerated%20Computing%20-%20Programming%20GPUs%20Lecture%2017.pdf
- https://netpbm.sourceforge.net/doc/pbm.html
- https://en.wikipedia.org/wiki/Netpbm
PNM<pnm::monochrome_t> chessboard{1920, 1080};
bool color = pnm::monochrome_t::BLACK;
for (int h = 0; h < chessboard.height(); ++h, color = !color)
for (int w = 0; w < chessboard.width(); ++w, color = !color)
chessboard(h, w, color);
chessboard.write_file_content("chessboard-bin.pbm");
chessboard.write_file_content("chessboard-ascii.pbm", 1);
PNM<pnm::monochrome_t> pbm{3, 2};
pbm(0,0, {255, 0, 0}); // since bits aren't addressable you will use a different syntax
pbm(0,1, {0, 255, 0});
pbm(0,2, {0, 255, 0});
pbm(1,0, {255, 255, 0});
pbm(1,1, {255, 255, 255});
pbm(1,2, {0, 0, 0});
pbm.write_file_content("bin.pbm");
pbm.write_file_content("ascii.pbm", 1);
PNM<pnm::rgb<pnm::BIT_8>> ppm{3, 2};
ppm(0,0) = {255, 0, 0};
ppm(0,1) = {0, 255, 0};
ppm(0,2) = {0, 0, 255};
ppm(1,0) = {255, 255, 0};
ppm(1,1) = {255, 255, 255};
ppm(1,2) = {0, 0, 0};
ppm.write_file_content("bin.ppm");
ppm.write_file_content("ascii.ppm", 1);
PNM<pnm::grayscale<pnm::BIT_8>> pgm{3, 2};
pgm(0,0) = {255, 0, 0};
pgm(0,1) = {0, 255, 0};
pgm(0,2) = {0, 0, 255};
pgm(1,0) = {255, 255, 0};
pgm(1,1) = {255, 255, 255};
pgm(1,2) = {0, 0, 0};
pgm.write_file_content("bin.pgm");
pgm.write_file_content("ascii.pgm", 1);
profiling, nvprof is a sort of compatibility layer to use old nvprof syntax, but most of nvprof flags are simply ignored by nsys
gpu profiling
nsys --help profile
nsys --help nvprof
# es.
nsys profile -o report.qdrep ./cuda
nsys nvprof ./cuda
nsys profile --stats=true ./cuda
nsys nvprof --print-gpu-trace ./cuda
cpu profiling
perf stat -e task-clock,cycles,instructions,r1b1,r10e,stalled-cycles-frontend,stalled-cycles-backend,L1-dcache-load-misses,cache-misses ./cuda
perf stat -r 10 valgrind --tool=callgrind ./cuda
valgrind --tool=callgrind ./cuda
valgrind --tool=callgrind ./cuda | kcachegrinddynamic analysis
valgrind --undef-value-errors=no --tool=memcheck --leak-check=yes --show-reachable=yes --num-callers=20 --track-fds=yes ./cuda
asm
objdump -S -M intel cuda | gedit - &