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Dynamic Kernel/Device Mapping Strategies for GPU-assisted HPC Systems

Jiadong Wu, Weiming Shi, Bo Hong

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Tags: Computer science, CUDA, nVidia, Performance

May 2, 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

Automatic NUMA Characterization using Cbench

Ryan Braithwaite, Wu-chun Feng, Patrick McCormick

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Package, Task scheduling, Tesla C2050

May 2, 2012 by hgpu

OpenCL and the 13 Dwarfs: A Work in Progress

W. Feng, H. Lin, T. Scogland, J. Zhang

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Tags: ATI, ATI Radeon HD 5450, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GT 520, OpenCL, Tesla C2050

May 1, 2012 by hgpu

Solving Stochastic Differential Equations Using General Purpose Graphics Processing Unit

Lev Alexandrovich Neiman

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Tags: Algorithms, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 480, Package, Tesla C1060, Tesla C2075

April 28, 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

Characterizing and Improving the Use of Demand-Fetched Caches in GPUs

Wenhao Jia, Kelly A. Shaw, Margaret Martonosi

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Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, Optimization, Performance, Tesla C2070

April 28, 2012 by hgpu

Hybrid CPU/GPU KD-Tree Construction for Versatile Ray Tracing

Jean-Patrick Roccia, Mathias Paulin, Christophe Coustet

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 560, Raytracing

April 27, 2012 by hgpu

Matrix Multiplication with CUDA – A basic introduction to the CUDA programming model

Robert Hochberg

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce 9600 M GT, nVidia GeForce GT 330 M, Tesla C1060

April 27, 2012 by hgpu

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Jeswin Godwin, Justin Holewinski, P. Sadayappan

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Tags: Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla C2050

April 25, 2012 by hgpu

Lynx: A Dynamic Instrumentation System for Data-Parallel Applications on GPGPU Architectures

Naila Farooqui, Andrew Kerr, Greg Eisenhauer, Karsten Schwan, Sudhakar Yalamanchili

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Package, Tesla C2050

April 25, 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

Dynamic Kernel/Device Mapping Strategies for GPU-assisted HPC Systems

GPU Acceleration for the C++ Standard Template Library

Automatic NUMA Characterization using Cbench

OpenCL and the 13 Dwarfs: A Work in Progress

Solving Stochastic Differential Equations Using General Purpose Graphics Processing Unit

High-Performance Code Generation for Stencil Computations on GPU Architectures

Characterizing and Improving the Use of Demand-Fetched Caches in GPUs

Hybrid CPU/GPU KD-Tree Construction for Versatile Ray Tracing

Matrix Multiplication with CUDA – A basic introduction to the CUDA programming model

High-performance sparse matrix-vector multiplication on GPUs for structured grid computations

Lynx: A Dynamic Instrumentation System for Data-Parallel Applications on GPGPU Architectures

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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