high performance computing on graphics processing units: hgpu.org

hgpu.org » Programming techniques

Piccolo: building fast, distributed programs with partitioned tables

Russell Power, Jinyang Li

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Tags: Algorithms, Clustering, Computer science, Programming techniques

September 9, 2011 by hgpu

Parallel Programming on a Soft-Core Based Multi-core System

Liang-Teh Lee, Shin-Tsung Lee, Ching-Wei Chen

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Tags: Algorithms, Computer science, FPGA, Programming techniques

September 8, 2011 by hgpu

Experiences with Mapping Non-linear Memory Access Patterns into GPUs

Eladio Gutierrez, Sergio Romero, Maria A. Trenas, Oscar Plata

Tags: Computer science, CUDA, Memory, nVidia, Optimization, Programming techniques

September 8, 2011 by hgpu

Programming Many-Core Chips

Andras Vajda

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Programming techniques

September 8, 2011 by hgpu

Automatic CPU-GPU communication management and optimization

Thomas B. Jablin, Prakash Prabhu, James A. Jablin, Nick P. Johnson, Stephen R. Beard, David I. August

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

September 7, 2011 by hgpu

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

John E. Stone, Jan Saam, David J. Hardy, Kirby L. Vandivort, Wen-mei W. Hwu, Klaus Schulten

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Tags: Algorithms, Chemistry, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Performance, Programming techniques, Rendering, Visualization

September 7, 2011 by hgpu

Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+

V. Aggarwal, A. George, K. Yalamanchili, C. Yoon, H. Lam, G. Stitt

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Tags: Computer science, FPGA, Heterogeneous systems, Performance, Programming Languages, Programming techniques

September 6, 2011 by hgpu

The impact of diverse memory architectures on multicore consumer software: an industrial perspective from the video games domain

George Russel, Colin Riley, Neil Henning, Uwe Dolinsky, Andrew Richards, Alastair F. Donaldson, Alexander S. van Amesfoort

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Tags: Cell processor, Computer science, Memory, Performance, Programming techniques

August 28, 2011 by hgpu

A new multi-core pipelined architecture for executing sequential programs for parallel geospatial computing

Duoduo Liao, Simon Y. Berkovich

Tags: Computer science, Programming techniques

August 28, 2011 by hgpu

A breadth-first course in multicore and manycore programming

Suzanne Rivoire

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Tags: Computer science, CUDA, High-level Languages, nVidia, OpenMP, Programming techniques

August 27, 2011 by hgpu

PFunc: modern task parallelism for modern high performance computing

Prabhanjan Kambadur, Anshul Gupta, Amol Ghoting, Haim Avron, Andrew Lumsdaine

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Tags: Computer science, Package, Performance, Programming techniques, Software Engineering

August 26, 2011 by hgpu

JCudaMP: OpenMP/Java on CUDA

Georg Dotzler, Ronald Veldema, Michael Klemm

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Tags: Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 280, OpenMP, Programming Languages, Programming techniques

August 23, 2011 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

Piccolo: building fast, distributed programs with partitioned tables

Parallel Programming on a Soft-Core Based Multi-core System

Experiences with Mapping Non-linear Memory Access Patterns into GPUs

Programming Many-Core Chips

Automatic CPU-GPU communication management and optimization

High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs

Bridging parallel and reconfigurable computing with multilevel PGAS and SHMEM+

The impact of diverse memory architectures on multicore consumer software: an industrial perspective from the video games domain

A new multi-core pipelined architecture for executing sequential programs for parallel geospatial computing

A breadth-first course in multicore and manycore programming

PFunc: modern task parallelism for modern high performance computing

JCudaMP: OpenMP/Java on CUDA

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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