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Targeted Testing of Compiler Optimizations via Grammar-Level Composition Styles

Zitong Zhou, Ben Limpanukorn, Hong Jin Kang, Jiyuan Wang, Yaoxuan Wu, Akos Kiss, Renata Hodovan, Miryung Kim

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Tags: Compilers, Computer science, LLVM, Optimization

December 7, 2025 by hgpu

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

Gabriel Rodriguez-Canal, David Katz, Nick Brown

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Tags: Computer science, Fortran, FPGA, Heterogeneous systems, HLS, HPC, LLVM, OpenMP, Package

November 16, 2025 by hgpu

Enabling Profile Guided Optimizations (PGO) for Graphics

Emma Jansson

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Tags: ARM, Compilers, Computer science, LLVM, Thesis, Vulkan

June 15, 2025 by hgpu

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Russel Arbore, Aaron Councilman, Xavier Routh, Ryan Ziegler, Praneet Rathi, Vikram Adve

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, LLVM, nVidia, nVidia GeForce RTX 2080 Ti, Package, Programming Languages, Rust

March 23, 2025 by hgpu

CPU-GPU co-execution through the exploitation of hybrid technologies via SYCL

Nozal Raúl, Jose Luis Bosque

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Tags: Computer science, CUDA, Heterogeneous systems, Hybrid computing, LLVM, load balancing, nVidia, nVidia GeForce GT 1030, oneAPI, OpenCL, performance portability, SYCL

February 3, 2025 by hgpu

The Rewriting of DataRaceBench Benchmark for OpenCL Program Validations

Chia-Chen Hsu, Chun-Lin Huang, Chao-Lin Lee, Jenq-Kuen Lee, Pei-Hung Lin

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Tags: Benchmarking, Computer science, LLVM, OpenCL, Performance

November 17, 2024 by hgpu

Exploring the Limits of Generic Code Execution on GPUs via Direct (OpenMP) Offload

S. Tian, B. Chapman, J. Doerfert

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Tags: Compilers, Computer science, LLVM, OpenMP

October 8, 2023 by hgpu

Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang

Nick Brown, Maurice Jamieson, Anton Lydike, Emilien Bauer, Tobias Grosser

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Tags: Computer science, Fortran, HPC, LLVM, MPI, nVidia, Package, Performance, Tesla V100

October 8, 2023 by hgpu

Compiler-assisted distribution of OpenMP code for improved scalability

Jannek Squar

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Tags: Compression, Computer science, Heterogeneous systems, LLVM, MPI, OpenMP, Package, Thesis

September 24, 2023 by hgpu

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Zane Fink, Konstantinos Parasyris, Giorgis Georgakoudis, Harshitha Menon

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Tags: AMD Radeon Instinct MI250X, ATI, Code generation, Computer science, HPC, LLVM, nVidia, nVidia V100, OpenMP, Package

September 6, 2023 by hgpu

Maximizing Parallelism and GPU Utilization For Direct GPU Compilation Through Ensemble Execution

Shilei Tian, Barbara Chapman, Johannes Doerfert

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Tags: Benchmarking, Computer science, CUDA, LLVM, nVidia, nVidia A100, OpenMP, Performance

July 24, 2023 by hgpu

Reinforcement Learning Strategies for Compiler Optimization in High level Synthesis

Hafsah Shahzad, Ahmed Sanaullah, Sanjay Arora, Robert Munafo, Xiteng Yao, Ulrich Drepper, Martin Herbordt

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Tags: Compilers, Computer science, FPGA, HLS, LLVM, Machine learning

March 26, 2023 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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high performance computing on graphics processing units: hgpu.org

Targeted Testing of Compiler Optimizations via Grammar-Level Composition Styles

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

Enabling Profile Guided Optimizations (PGO) for Graphics

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

CPU-GPU co-execution through the exploitation of hybrid technologies via SYCL

The Rewriting of DataRaceBench Benchmark for OpenCL Program Validations

Exploring the Limits of Generic Code Execution on GPUs via Direct (OpenMP) Offload

Fortran performance optimisation and auto-parallelisation by leveraging MLIR-based domain specific abstractions in Flang

Compiler-assisted distribution of OpenMP code for improved scalability

HPAC-Offload: Accelerating HPC Applications with Portable Approximate Computing on the GPU

Maximizing Parallelism and GPU Utilization For Direct GPU Compilation Through Ensemble Execution

Reinforcement Learning Strategies for Compiler Optimization in High level Synthesis

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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