high performance computing on graphics processing units: hgpu.org

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Mapping a Data-Flow Programming Model onto Heterogeneous Platforms

Alina Sbirlea, Yi Zou, Zoran Budimlic, Jason Cong, Vivek Sarkar

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Tags: Algorithms, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Programming techniques, Tesla C1060

May 14, 2012 by hgpu

CAPRI: Prediction of Compaction-Adequacy for Handling Control-Divergence in GPGPU Architectures

Minsoo Rhu, Mattan Erez

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, Programming techniques

May 11, 2012 by hgpu

iGPU: Exception Support and Speculative Execution on GPUs

Jaikrishnan Menon, Marc de Kruijf, Karthikeyan Sankaralingam

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Tags: ATI, ATI Radeon HD 6550, Computer science, nVidia, nVidia GeForce GTX 580, OpenCL, Performance, Programming techniques

May 7, 2012 by hgpu

GPU Acceleration for the C++ Standard Template Library

Christian DeLozier

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 570, OpenCL, Package, Programming techniques, Software Engineering

May 2, 2012 by hgpu

High-Performance Code Generation for Stencil Computations on GPU Architectures

Justin Holewinski, Louis-Noel Pouchet, P. Sadayappan

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Tags: Algorithms, ATI, ATI Radeon HD 6550, Code generation, Compilers, Computer science, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, OpenCL, Programming Languages, Programming techniques, Tesla C2050

April 28, 2012 by hgpu

RGEM: A Responsive GPGPU Execution Model for Runtime Engines

Shinpei Kato, Karthik Lakshmanan, Aman Kumar, Mihir Kelkar, Yutaka Ishikawa, Ragunathan (Raj) Rajkumar

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Programming techniques

April 11, 2012 by hgpu

A Programmable Processing Array Architecture Supporting Dynamic Task Scheduling and Module-Level Prefetching

Junghee Lee, Hyung Gyu Lee, Soonhoi Ha, Jongman Kim, Chrysostomos Nicopoulos

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro NVS 295, Prefetch, Programming techniques, Task scheduling

April 5, 2012 by hgpu

Auto-tuning a High-Level Language Targeted to GPU Codes

Scott Grauer-Gray, Lifan Xu, Robert Searles, Sudhee Ayalasomayajula, John Cavazos

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GTX 280, OpenCL, Optimization, Performance, Programming techniques, Stereo vision, Tesla C2050

March 28, 2012 by hgpu

OpenMPC: Extended OpenMP for Efficient Programming and Tuning on GPUs

Seyong Lee, Rudolf Eigenmann

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro FX 5600, OpenMP, Performance, Programming techniques

March 26, 2012 by hgpu

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

John Jenkins, Pavan Balaji, James Dinan, Nagiza F. Samatova, Rajeev Thakur

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Tags: Computer science, CUDA, MPI, nVidia, Performance, Programming Languages, Programming techniques, Tesla C2050

March 18, 2012 by hgpu

Better speedups using simpler parallel programming for graph connectivity and biconnectivity

James A. Edwards, Uzi Vishkin

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Performance, Programming techniques

March 11, 2012 by hgpu

Paragon: Collaborative Speculative Loop Execution on GPU and CPU

Mehrzad Samadi, Amir Hormati, Janghaeng Lee, Scott Mahlke

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, Optimization, Programming techniques

March 8, 2012 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

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

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high performance computing on graphics processing units: hgpu.org

Mapping a Data-Flow Programming Model onto Heterogeneous Platforms

CAPRI: Prediction of Compaction-Adequacy for Handling Control-Divergence in GPGPU Architectures

iGPU: Exception Support and Speculative Execution on GPUs

GPU Acceleration for the C++ Standard Template Library

High-Performance Code Generation for Stencil Computations on GPU Architectures

RGEM: A Responsive GPGPU Execution Model for Runtime Engines

A Programmable Processing Array Architecture Supporting Dynamic Task Scheduling and Module-Level Prefetching

Auto-tuning a High-Level Language Targeted to GPU Codes

OpenMPC: Extended OpenMP for Efficient Programming and Tuning on GPUs

Enabling Fast, Noncontiguous GPU Data Movement in Hybrid MPI+GPU Environments

Better speedups using simpler parallel programming for graph connectivity and biconnectivity

Paragon: Collaborative Speculative Loop Execution on GPU and CPU

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

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

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