search for: fatbinary

...ither clang's CUDA frontend or NVCC to ptx. Here is the workflow in five stages: 1. generating ptx device code (a kind of nvidia assembler) 2. translate ptx to sass (machine code of ptx) 3. generate a fatbinray (a kind of wrapper for the device code) 4. generate host code object file (use fatbinary as input) 5. link to executable (The exact commands are stored in the commands.txt in the github repo) The interpreter replaces the 4th and 5th step. It interprets the host code with pre-compiled device code as fatbinary. The fatbinary (Step 1 to 3) will be generated with the clang compiler and...

...> Here is the workflow in five stages: > > 1. generating ptx device code (a kind of nvidia assembler) > 2. translate ptx to sass (machine code of ptx) > 3. generate a fatbinray (a kind of wrapper for the device code) > 4. generate host code object file (use fatbinary as input) > 5. link to executable > > (The exact commands are stored in the commands.txt in the github repo) > > The interpreter replaces the 4th and 5th step. It interprets the > host code with pre-compiled device code as fatbinary. The > fatbinary (Step 1...

...d-a-device.bc after this step; 3) Generate IR files for b.cu: clang++ -g -emit-llvm --cuda-gpu-arch=sm_35 -c b.cu; 4) Link instrumented-a.device.bc with the device code generated for b.cu: llvm-link intrumented-a-device.bc b-cuda-nvptx64-nvidia-cuda-sm_35.bc -o ab-device.bc; 5) Use llc, ptxas & fatbinary on ab-device.bc to get ab-device.ptx, ab-device.o & ab-device.fatbin; 6) Call clang again the generate the host object file ab.o, with ab-device.o & ab-device.fatbin embedded; 7) Link against libraries and get the final binary: a.out. The binary a.out fails with an exception I when run it...

...e clang command. When you add CUDA to the equation, you add several other steps. If you use the clang front end to compile, clang does the following: 1. compiles the driver source code 2. compiles the resulting PTX code using the CUDA ptxas command 3. builds a "fat binary" using the CUDA fatbinary command 4. compiles the host source code and links in the fat binary So my question is: how do we replicate that process in memory, to generate modules that we can add to our JIT? I am no CUDA expert, and not much of a clang expert either, so if anyone out there can point me in the right directio...

...link the modified axpy-sm_20.bc to the final binary, you need several extra steps: 1. Compile axpy-sm_20.bc to PTX assembly using llc: llc axpy-sm_20.bc -o axpy-sm_20.ptx -march=<nvptx or nvptx64> 2. Compile the PTX assembly to SASS using ptxas 3. Make the SASS a fat binary using NVIDIA's fatbinary tool 4. Link the fat binary to the host code using ld. Clang does step 2-4 by invoking subcommands. Therefore, you can use "clang -###" to dump all the subcommands, and then find the ones for step 2-4. For example, $ clang++ -### -O3 axpy.cu -I/usr/local/cuda/samples/common/inc -L/usr/l...

...can be used to generate a SPIR-V binary for OpenCL code. There was a separate thread regarding generation of SPIR-V binary and the community suggested that a translator from LLVM IR to SPIR-V can be used as an external tool, called llvm-spirv. This can be invoked similar to such tools as ptxas and fatbinary for the CUDA toolchain: http://lists.llvm.org/pipermail/llvm-dev/2018-February/121440.html An example of how Clang can be used to target SPIR-V: clang -c test.cl -target spirv[32|64]-unknown-unknown -o test.spv This will result in the following Clang actions: (1) clang -cc1 -triple spirv[32|64]...

...uation, you add several other steps. If you use the clang >> front end to compile, clang does the following: >> >> 1. compiles the driver source code >> 2. compiles the resulting PTX code using the CUDA ptxas command >> 3. builds a "fat binary" using the CUDA fatbinary command >> 4. compiles the host source code and links in the fat binary >> >> So my question is: how do we replicate that process in memory, to >> generate modules that we can add to our JIT? >> >> I am no CUDA expert, and not much of a clang expert either, so if...

...rate a SPIR-V binary for OpenCL code. There was a separate > thread regarding generation of SPIR-V binary and the community suggested > that a translator from LLVM IR to SPIR-V can be used as an external tool, > called llvm-spirv. This can be invoked similar to such tools as ptxas and > fatbinary for the CUDA toolchain: > http://lists.llvm.org/pipermail/llvm-dev/2018-February/121440.html > > An example of how Clang can be used to target SPIR-V: > > clang -c test.cl -target spirv[32|64]-unknown-unknown -o test.spv > > This will result in the following Clang actions: >...

...mpxft_00007040_00000000-13_cuda_id_test.cpp3.i" -o "/tmp/tmpxft_00007040_00000000-6_cuda_id_test.ptx" #$ ptxas -arch=sm_35 -m64 --compile-only "/tmp/tmpxft_00007040_00000000-6_cuda_id_test.ptx" -o "/tmp/tmpxft_00007040_00000000-14_cuda_id_test.sm_35.cubin" #$ fatbinary --create="/tmp/tmpxft_00007040_00000000-2_cuda_id_test.fatbin" -64 --cmdline="--compile-only " "--image=profile=sm_35,file=/tmp/tmpxft_00007040_00000000-14_cuda_id_test.sm_35.cubin" "--image=profile=compute_35,file=/tmp/tmpxft_00007040_00000000-6_cuda_id_test.ptx...

...can be used to generate a SPIR-V binary for OpenCL code. There was a separate thread regarding generation of SPIR-V binary and the community suggested that a translator from LLVM IR to SPIR-V can be used as an external tool, called llvm-spirv. This can be invoked similar to such tools as ptxas and fatbinary for the CUDA toolchain: >>> http://lists.llvm.org/pipermail/llvm-dev/2018-February/121440.html >>> >>> An example of how Clang can be used to target SPIR-V: >>> >>> clang -c test.cl <http://test.cl> -target spirv[32|64]-unknown-unknown -...

...CUDA > to the equation, you add several other steps. If you use the clang front > end to compile, clang does the following: > > 1. compiles the driver source code > 2. compiles the resulting PTX code using the CUDA ptxas command > 3. builds a "fat binary" using the CUDA fatbinary command > 4. compiles the host source code and links in the fat binary > > So my question is: how do we replicate that process in memory, to generate > modules that we can add to our JIT? > > I am no CUDA expert, and not much of a clang expert either, so if anyone > out there c...

...rate a SPIR-V binary for OpenCL code. There was a > separate thread regarding generation of SPIR-V binary and the community > suggested that a translator from LLVM IR to SPIR-V can be used as an > external tool, called llvm-spirv. This can be invoked similar to such tools > as ptxas and fatbinary for the CUDA toolchain: > >>>> http://lists.llvm.org/pipermail/llvm-dev/2018-February/121440.html > >>>> > >>>> An example of how Clang can be used to target SPIR-V: > >>>> > >>>> clang -c test.cl <http://test.cl...

...rate a SPIR-V binary for OpenCL code. There was a > separate thread regarding generation of SPIR-V binary and the community > suggested that a translator from LLVM IR to SPIR-V can be used as an > external tool, called llvm-spirv. This can be invoked similar to such tools > as ptxas and fatbinary for the CUDA toolchain: > >> http://lists.llvm.org/pipermail/llvm-dev/2018-February/121440.html > >> > >> An example of how Clang can be used to target SPIR-V: > >> > >> clang -c test.cl <http://test.cl> -target > spirv[32|64]-unknow...

...binary, you need several >> extra steps: >> 1. Compile axpy-sm_20.bc to PTX assembly using llc: llc axpy-sm_20.bc -o >> axpy-sm_20.ptx -march=<nvptx or nvptx64> >> 2. Compile the PTX assembly to SASS using ptxas >> 3. Make the SASS a fat binary using NVIDIA's fatbinary tool >> 4. Link the fat binary to the host code using ld. >> >> Clang does step 2-4 by invoking subcommands. Therefore, you can use >> "clang -###" to dump all the subcommands, and then find the ones for step >> 2-4. For example, >> >> $ clang++ -...