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ML-Triton, A Multi-Level Compilation and Language Extension to Triton GPU Programming

Dewei Wang, Wei Zhu, Liyang Ling, Ettore Tiotto, Quintin Wang, Whitney Tsang, Julian Opperman, Jacky Deng

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Tags: AI, Code generation, Compilers, Computer science, CUDA, Intel Data Center GPU Max 1550, nVidia, oneAPI, SYCL

March 23, 2025 by hgpu

Mpache: Interaction Aware Multi-level Cache Bypassing on GPUs

Mengyue Xi, Tianyu Guo, Xuanteng Huang, Zejia Lin, Xianwei Zhang

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Tags: cache, Compilers, Computer science, nVidia, PTX

March 10, 2025 by hgpu

pyATF: Constraint-Based Auto-Tuning in Python

Richard Schulze, Sergei Gorlatch, Ari Rasch

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Tags: Auto-Tuning, Compilers, Computer science, CUDA, nVidia A100, OpenCL, Package, Performance, Python

March 3, 2025 by hgpu

Towards Studying the Effect of Compiler Optimizations and Software Randomization on GPU Reliability

Pau López Castillón, Xavier Caricchio Hernández, Leonidas Kosmidis

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080 Ti

March 3, 2025 by hgpu

Optimizing the optimizer increasing performance efficiency of modern compilers

Hafsah Shahzad

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Tags: Compilers, Computer science, FPGA, HLS, Intel, nVidia, nVidia GeForce RTX 4070, Thesis

February 10, 2025 by hgpu

Compiler Support for Speculation in Decoupled Access/Execute Architectures

Robert Szafarczyk, Syed Waqar Nabi, Wim Vanderbauwhede

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Tags: Compilers, Computer science, HLS, Performance, Prefetch

February 10, 2025 by hgpu

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

Manos Pavlidakis, Chris Kitching, Nicholas Tomlinson, Michael Søndergaard

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Tags: ATI, Compilers, Computer science, CUDA, HIP, nVidia, Package, Portability, PTX

January 13, 2025 by hgpu

Scheduling Languages: A Past, Present, and Future Taxonomy

Mary Hall, Cosmin Oancea, Anne C. Elster, Ari Rasch, Sameeran Joshi, Amir Mohammad Tavakkoli, Richard Schulze

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Tags: Auto-Tuning, Compilers, Computer science, Performance, Programming Languages, Task scheduling

November 3, 2024 by hgpu

CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations

Aaron Jarmusch, Felipe Cabarcas, Swaroop Pophale, Andrew Kallai, Johannes Doerfert, Luke Peyralans, Seyong Lee, Joel Denny, Sunita Chandrasekaran

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Tags: AMD Radeon Instinct MI210, AMD Radeon Instinct MI250X, ATI, Compilers, Computer science, Fortran, Heterogeneous systems, HPC, nVidia, nVidia H100, OpenMP

August 25, 2024 by hgpu

Acceleration for the many, not the few

Jackson Woodruff

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Tags: Compilers, Computer science, Heterogeneous systems, Package, Thesis

August 14, 2024 by hgpu

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Junqing Lin, Jingwei Sun, Xiaolong Shi, Honghe Zhang, Xianzhi Yu, Xinzhi Wang, Jun Yao, Guangzhong Sun

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Tags: Compilers, Computer science, CUDA, Deep learning, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti, Performance, Sparse matrix, Tesla V100

August 4, 2024 by hgpu

Automatic Code Rewriting for Performance Portability

Alister Johnson

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Tags: Compilers, Computer science, HIP, OpenCL, OpenMP, performance portability, SYCL, Thesis

July 7, 2024 by hgpu

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

pyATF: Constraint-Based Auto-Tuning in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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high performance computing on graphics processing units: hgpu.org

ML-Triton, A Multi-Level Compilation and Language Extension to Triton GPU Programming

Mpache: Interaction Aware Multi-level Cache Bypassing on GPUs

pyATF: Constraint-Based Auto-Tuning in Python

Towards Studying the Effect of Compiler Optimizations and Software Randomization on GPU Reliability

Optimizing the optimizer increasing performance efficiency of modern compilers

Compiler Support for Speculation in Decoupled Access/Execute Architectures

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

Scheduling Languages: A Past, Present, and Future Taxonomy

CI/CD Efforts for Validation, Verification and Benchmarking OpenMP Implementations

Acceleration for the many, not the few

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Automatic Code Rewriting for Performance Portability

Recent source codes

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

SUperman: Highly Efficient Permanent Computation Library

TransCL: An Automatic CUDA-to-OpenCL Programs Transformation Framework

pyATF: The Auto-Tuning Framework (ATF) in Python

TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators

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