high performance computing on graphics processing units: hgpu.org

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Optimising Purely Functional GPU Programs (Thesis)

Trevor L. McDonell

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Performance, Tesla T10, Thesis

August 10, 2014 by hgpu

Direct Numerical Simulation of Turbulent Flows with Parallel Algorithms for Various Computing Architectures

A. Gorobets, F.X. Trias, R. Borrell, G. Oyarzun, A. Oliva

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, ATI Radeon HD 7970, Fluid dynamics, Intel Xeon Phi, MPI, Numerical simulation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX Titan, OpenCL, OpenMP, Performance, Tesla C1060, Tesla C2050

August 10, 2014 by hgpu

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

D. C. Price, M. A. Clark, B. R. Barsdell, R. Babich, L. J. Greenhill

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Tags: Astrophysics, CUDA, Energy-efficient computing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 780, Package, Performance, Signal processing, Tesla K20

August 1, 2014 by hgpu

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Peng Di

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tesla C2050, Thesis

July 30, 2014 by hgpu

Aristotle: A Performance Impact Indicator for the OpenCL Kernels Using Local Memory

Jianbin Fang, Henk Sips, Ana Lucia Varbanescu

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Xeon Phi, Local memory, nVidia, OpenCL, Performance, Portability, Tesla C1060, Tesla C2050, Tesla K20

July 29, 2014 by jfang

GPU Computing to Improve Game Engine Performance

Abu Asaduzzaman, Hin Y. Lee

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Tags: Computer science, CUDA, Data parallelism, Games, Image processing, nVidia, nVidia GeForce 8800 GTX, Performance

July 28, 2014 by hgpu

Performance-efficient mechanisms for managing irregularity in throughput processors

Minsoo Rhu

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Prefetch, Thesis

July 20, 2014 by hgpu

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

Tsutomu Inamoto, Yoshinobu Higami, Shin-ya Kobayashi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance

July 17, 2014 by hgpu

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

David Rohr

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Review, Thesis

July 14, 2014 by hgpu

GPU Techniques Applied to Euler Flow Simulations and Comparison to CPU Performance

Blake Koop

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Tags: CUDA, Fluid dynamics, nVidia, Performance, Tesla C2070

July 14, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Understanding the SIMD Efficiency of Graph Traversal on GPU

Yichao Cheng, Hong An, Zhitao Chen, Feng Li, Zhaohui Wang, Xia Jiang, Yi Peng

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C2050

July 10, 2014 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

Optimising Purely Functional GPU Programs (Thesis)

Direct Numerical Simulation of Turbulent Flows with Parallel Algorithms for Various Computing Architectures

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Aristotle: A Performance Impact Indicator for the OpenCL Kernels Using Local Memory

GPU Computing to Improve Game Engine Performance

Performance-efficient mechanisms for managing irregularity in throughput processors

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

GPU Techniques Applied to Euler Flow Simulations and Comparison to CPU Performance

Benchmarking the Memory Hierarchy of Modern GPUs

Understanding the SIMD Efficiency of Graph Traversal on GPU

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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