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TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Jianling Li, Shangzhan Li, Zhenye Gao, Qi Shi, Yuxuan Li, Zefan Wang, Jiacheng Huang, Haojie Wang, Jianrong Wang, Xu Han, Zhiyuan Liu, Maosong Sun

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Tags: Benchmarking, Code generation, Computer science, CUDA, Deep learning, LLM, nVidia, nVidia A100, Package, Python

March 3, 2025 by hgpu

Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation

Nicolas Nytko, Andrew Reisner, J. David Moulton, Luke N. Olson, Matthew West

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Tags: Code generation, Computer science, CUDA, Fortran, Heterogeneous systems, MPI, nVidia, nVidia A100, OpenCL

February 16, 2025 by hgpu

Fully-Automated Code Generation for Efficient Computation of Sparse Matrix Permanents on GPUs

Deniz Elbek, Kamer Kaya

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia A100, nVidia Quadro GV100, PTX, Sparse matrix

February 3, 2025 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

Naifeng Zhang, Franz Franchetti

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Tags: Code generation, Computer science, CUDA, Linear Algebra, Modular arithmetic, nVidia, nVidia GeForce RTX 4090, nVidia H100, nVidia V100, Package, Security

January 20, 2025 by hgpu

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Aman Chaturvedi, Daniel Nichols, Siddharth Singh, Abhinav Bhatele

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Tags: Code generation, Computer science, CUDA, HIP, HPC, LLM, MPI, nVidia, nVidia A100, OpenMP, Package

December 24, 2024 by hgpu

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Sanil Rao, Mike Franusich, , Mohammad Alaul Haque Monil, Het Mankad, Jeffrey S. Vetter, Franz Franchetti

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Tags: AMD, ATI, Code generation, Computer science, CUDA, Differential equations, Fortran, Heterogeneous systems, HIP, nVidia, OpenCL, OpenMP, Partial differential equations, PDEs

December 8, 2024 by hgpu

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Anjiang Wei, Allen Nie, Thiago S. F. X. Teixeira, Rohan Yadav, Wonchan Lee, Ke Wang, Alex Aiken

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Tags: Code generation, Computer science, DSL, LLM, Matrix multiplication, nVidia, Optimization, Tesla P100

November 17, 2024 by hgpu

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Arun Thangamani

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Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenCL, Thesis

October 13, 2024 by hgpu

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Marek Palkowski, Mateusz Gruzewski

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Tags: AMD Radeon RX 6800, ATI, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenCL, OpenMP

September 29, 2024 by hgpu

A Comparison of OpenCL, CUDA, and HIP as Compilation Targets for a Functional Array Language

Troels Henriksen

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Tags: AMD Radeon Instinct MI100, ATI, Code generation, Computer science, CUDA, HIP, nVidia, nVidia A100, OpenCL, Package, Programming Languages

July 28, 2024 by hgpu

Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models

Kangwei Xu, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li

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Tags: Code generation, Computer science, FPGA, HLS, LLM

July 14, 2024 by hgpu

APPy: Annotated Parallelism for Python on GPUs

Tong Zhou, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 3090, Python

February 25, 2024 by hgpu

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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high performance computing on graphics processing units: hgpu.org

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation

Fully-Automated Code Generation for Efficient Computation of Sparse Matrix Permanents on GPUs

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Improving Parallel Program Performance Through DSL-Driven Code Generation with LLM Optimizers

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

A Comparison of OpenCL, CUDA, and HIP as Compilation Targets for a Functional Array Language

Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models

APPy: Annotated Parallelism for Python on GPUs

Recent source codes

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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