In its generated code, nvcc may omit not_inline_hd’sĬall to host_only entirely, or it may try to generate code for Nvcc only emits a warning for not_inline_hd device code is allowed to call (usually as part of the process of invoking them).Ĭlang’s behavior with respect to the wrong-side rule matches nvcc’s, except Inline functions: They aren’t codegen’ed unless they’re instantiated ffp-contract=įor the purposes of the wrong-side rule, templated functions also behave like GPU hardware allows for more control over numerical operations than most CPUs,īut this results in more compiler options for you to juggle. If you’re using GPUs, you probably care about making numerical code run fast. The CUDA SDK into /usr/local/cuda or /usr/local/cuda-X.Y. You may also need to pass -cuda-path=/path/to/cuda if you didn’t install The -L and -l flags only need to be passed when linking. You can pass -cuda-gpu-arch multiple times to compile for multiple archs. a binary compiled with -cuda-gpu-arch=sm_30 would beįorwards-compatible with e.g. Note: You cannot pass compute_XX as an argument to -cuda-gpu-arch Want to run your program on a GPU with compute capability of 3.5, specify V10.0 CUDA SDK no longer supports compilation of 32-bit The host, you’re also compiling 64-bit code for the device.) Note that as of (In CUDA, the device code and host codeĪlways have the same pointer widths, so if you’re compiling 64-bit code for L/usr/local/cuda/lib64 if compiling in 64-bit mode otherwise, – the directory where you installed CUDA SDK. “CUDA driver version is insufficient for CUDA runtime version” errors when you On MacOS, replace -lcudart_static with -lcudart otherwise, you may get
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