├── .gitignore ├── Dockerfile ├── LICENSE └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | CMakeLists.txt.user 2 | CMakeCache.txt 3 | CMakeFiles 4 | CMakeScripts 5 | Testing 6 | Makefile 7 | cmake_install.cmake 8 | install_manifest.txt 9 | compile_commands.json 10 | CTestTestfile.cmake 11 | _deps 12 | CMakeUserPresets.json 13 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # syntax=docker/dockerfile:1.4 2 | FROM nvidia/cuda:12.6.2-devel-ubuntu24.04 as devel 3 | ENV PATH=/root/GoPTX_nvcc/bin:$PATH \ 4 | CPATH=/root/GoPTX_nvcc/include:$CPATH \ 5 | LIBRARY_PATH=/root/GoPTX_nvcc/lib:$LIBRARY_PATH \ 6 | LD_LIBRARY_PATH=/root/GoPTX_nvcc/lib:$LD_LIBRARY_PATH \ 7 | ANTLR4_JAR_LOCATION=/root/antlr-4.10.1-complete.jar 8 | COPY . /root/GoPTX 9 | RUN < a.cu 29 | nvcc -ptx a.cu 30 | echo "__global__ void nameb(float *b) { *b += 1; }" > b.cu 31 | nvcc -ptx b.cu 32 | GoPTX_link a.ptx b.ptx _sa _sb > c.ptx 33 | GoPTX_merge c.ptx \$1_\$2_merged namea nameb > d.ptx 34 | cat d.ptx 35 | EOF 36 | FROM nvidia/cuda:12.6.2-base-ubuntu24.04 as base 37 | ENV PATH=/root/GoPTX_nvcc/bin:$PATH \ 38 | CPATH=/root/GoPTX_nvcc/include:$CPATH \ 39 | LIBRARY_PATH=/root/GoPTX_nvcc/lib:$LIBRARY_PATH \ 40 | LD_LIBRARY_PATH=/root/GoPTX_nvcc/lib:$LD_LIBRARY_PATH 41 | RUN < results.html && python3 ../analyse.py < results.html"] 53 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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For more details, you can see our DAC'25 paper "GoPTX: Fine-grained GPU Kernel Fusion by PTX Level Instruction Flow Weaving". The source code and docker image will come soon. 4 | 5 | ## Quick start 6 | 7 | ### Docker 8 | 9 | ```mermaid 10 | flowchart LR 11 | subgraph GoPTX_link 12 | c.ptx 13 | end 14 | subgraph GoPTX_merge 15 | d.ptx 16 | end 17 | a.ptx--suffix_a-->c.ptx 18 | b.ptx--suffix_b-->c.ptx 19 | c.ptx--regex_merged-->d.ptx 20 | c.ptx--regex_a-->d.ptx 21 | c.ptx--regex_b-->d.ptx 22 | ``` 23 | 24 | Workflow: 25 | 26 | 1. If the two kernels are not in the same PTX file, use `GoPTX_link`. It can add suffixes to avoid name conflict. 27 | 2. `GoPTX_merge` uses regex to match the input kernels and regex to generate the name of the fused kernel. 28 | 29 | ```shell 30 | docker run \ 31 | --runtime=nvidia \ 32 | --gpus "device=0" \ 33 | --name goptx \ 34 | -it \ 35 | wukan0621/goptx:v0.0.1-dac25 sh 36 | cd /GoPTX_nvcc/utils 37 | GoPTX_link a.ptx b.ptx _sa _sb > c.ptx 38 | GoPTX_merge c.ptx \$1_\$2_merged namea nameb > d.ptx 39 | ``` 40 | 41 | You can see how GoPTX weaves `_Z5nameaPi_sa` and `_Z5namebPf_sb`. 42 | 43 | ```txt 44 | .version 8.5 45 | .target sm_52 46 | .address_size 64 47 | .visible .entry _Z5nameaPi_sa( .param .u64 _Z5nameaPi_param_0_sa){ 48 | .reg .b32 %r_sa<3>; 49 | .reg .b64 %rd_sa<3>; 50 | ld.param.u64 %rd_sa1,[ _Z5nameaPi_param_0_sa]; 51 | cvta.to.global.u64 %rd_sa2, %rd_sa1; 52 | ld.global.u32 %r_sa1,[ %rd_sa2]; 53 | add.s32 %r_sa2, %r_sa1, 1; 54 | st.global.u32[ %rd_sa2], %r_sa2; 55 | ret; 56 | } 57 | .visible .entry _Z5namebPf_sb( .param .u64 _Z5namebPf_param_0_sb){ 58 | .reg .f32 %f_sb<3>; 59 | .reg .b64 %rd_sb<3>; 60 | ld.param.u64 %rd_sb1,[ _Z5namebPf_param_0_sb]; 61 | cvta.to.global.u64 %rd_sb2, %rd_sb1; 62 | ld.global.f32 %f_sb1,[ %rd_sb2]; 63 | add.f32 %f_sb2, %f_sb1, 0f3F800000; 64 | st.global.f32[ %rd_sb2], %f_sb2; 65 | ret; 66 | } 67 | .visible .entry _Z5nameaPi_sa__Z5namebPf_sb_merged( .param .u64 _Z5nameaPi_param_0_saf, .param .u64 _Z5namebPf_param_0_sbs){ 68 | .reg .b32 %r_saf<3>; 69 | .reg .b64 %rd_saf<3>; 70 | .reg .f32 %f_sbs<3>; 71 | .reg .b64 %rd_sbs<3>; 72 | $0__GoPTX: 73 | ld.param.u64 %rd_saf1,[ _Z5nameaPi_param_0_saf]; 74 | ld.param.u64 %rd_sbs1,[ _Z5namebPf_param_0_sbs]; 75 | cvta.to.global.u64 %rd_saf2, %rd_saf1; 76 | cvta.to.global.u64 %rd_sbs2, %rd_sbs1; 77 | ld.global.u32 %r_saf1,[ %rd_saf2]; 78 | ld.global.f32 %f_sbs1,[ %rd_sbs2]; 79 | add.s32 %r_saf2, %r_saf1, 1; 80 | add.f32 %f_sbs2, %f_sbs1, 0f3F800000; 81 | st.global.u32[ %rd_saf2], %r_saf2; 82 | st.global.f32[ %rd_sbs2], %f_sbs2; 83 | ret; 84 | } 85 | ``` 86 | 87 | Get the results of the DAC'25 paper "GoPTX: Fine-grained GPU Kernel Fusion by PTX Level Instruction Flow Weaving". It requires a GPU of architecture sm_80 or sm_90 (we use A100-PCIE-40GB and have not tuned for other devices). For other architecture, you should rebuild from the source and specify your `$CUDAARCHS`. Our result is available at `/root/GoPTX_nvcc/utils/results/results.adaptive.html`. 88 | 89 | ```shell 90 | docker run \ 91 | --runtime=nvidia \ 92 | --gpus "device=0" \ 93 | --name goptx \ 94 | wukan0621/goptx:v0.0.1-dac25 95 | docker cp goptx:/root/GoPTX_nvcc/utils . 96 | ``` 97 | 98 | ### Build from source 99 | 100 | See [Dockerfile](./Dockerfile). 101 | 102 | ## Command line usage 103 | 104 | ```shell 105 | GoPTX_link [suffix_a=""] [suffix_b=""] > c.ptx 106 | GoPTX_merge [strategy=0] > d.ptx 107 | ``` 108 | --------------------------------------------------------------------------------