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Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Shilei Tian, Joseph Huber, Barbara Chapman, Johannes Doerfert

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Tags: AMD Radeon Instinct MI100, ATI, Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, OpenMP

July 17, 2022 by hgpu

CuPBoP: CUDA for Parallelized and Broad-range Processors

Ruobing Han, Jun Chen, Bhanu Garg, Jeffrey Young, Jaewoong Sim, Hyesoon Kim

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Tags: Benchmarking, Compilers, Computer science, CUDA, Heterogeneous systems, HIP, MPI, nVidia, nVidia GeForce GTX 1660 Ti, OpenMP

June 19, 2022 by hgpu

On the Compilation Performance of Current SYCL Implementations

Peter Thoman, Facundo Molina Heredia, Thomas Fahringer

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Tags: Code generation, Compilers, Computer science, Heterogeneous systems, OpenCL, Package, Performance, SYCL

June 12, 2022 by hgpu

SYCLops: A SYCL Specific LLVM to MLIR Converter

Alexandre Singer, Frank (Fang) Gao, Kai-Ting Amy Wang

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Tags: Compilers, Computer science, Heterogeneous systems, LLVM, SYCL

May 15, 2022 by hgpu

CASE: A Compiler-Assisted SchEduling Framework for Multi-GPU Systems

Chao Chen, Chris Porter, Santosh Pande

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Tags: Compilers, Computer science, CUDA, nVidia, Package, Task scheduling, Tesla P100, Tesla V100

May 1, 2022 by hgpu

One-shot tuner for deep learning compilers

Jaehun Ryu, Eunhyeok Park, Hyojin Sung

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Tags: Compilers, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 2080 Ti, Package

March 27, 2022 by hgpu

GC3: An Optimizing Compiler for GPU Collective Communication

Meghan Cowan, Saeed Maleki, Madanlal Musuvathi, Olli Saarikivi, Yifan Xiong

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Tags: Algorithms, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia A100

February 6, 2022 by hgpu

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Mhd Ghaith Olabi, Juan Gómez Luna, Onur Mutlu, Wen-mei Hwu, Izzat El Hajj

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Tags: Compilers, Computer science, CUDA, nVidia, Package, Performance, Tesla V100

January 16, 2022 by hgpu

PROGRAML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael O'Boyle, Hugh Leather

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Tags: Compilers, Computer science, Flow analysis, Machine learning, OpenCL, Package, Performance

January 2, 2022 by hgpu

COX: CUDA on X86 by Exposing Warp-Level Functions to CPUs

Ruobing Han, Jaewon Lee, Jaewoong Sim, Hyesoon Kim

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia

December 26, 2021 by hgpu

Generating GPU Compiler Heuristics using Reinforcement Learning

Ian Colbert, Jake Daly, Norm Rubin

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Tags: AMD Radeon 6800 XT, AMD Radeon RX 5700 XT, ATI, Compilers, Computer science, Machine learning, Performance

November 28, 2021 by hgpu

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding

Pratik Fegade, Tianqi Chen, Phillip B. Gibbons, Todd C. Mowry

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Tags: Compilers, Computer science, CUDA, Deep learning, nVidia, Tesla V100

October 24, 2021 by hgpu

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

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high performance computing on graphics processing units: hgpu.org

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

CuPBoP: CUDA for Parallelized and Broad-range Processors

On the Compilation Performance of Current SYCL Implementations

SYCLops: A SYCL Specific LLVM to MLIR Converter

CASE: A Compiler-Assisted SchEduling Framework for Multi-GPU Systems

One-shot tuner for deep learning compilers

GC3: An Optimizing Compiler for GPU Collective Communication

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

PROGRAML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

COX: CUDA on X86 by Exposing Warp-Level Functions to CPUs

Generating GPU Compiler Heuristics using Reinforcement Learning

The CoRa Tensor Compiler: Compilation for Ragged Tensors with Minimal Padding

Recent source codes

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

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