high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Orchestrated Scheduling and Prefetching for GPGPUs

Adwait Jog, Onur Kayiran, Asit K. Mishra, Mahmut T. Kandemir, Onur Mutlu, Ravishankar Iyer, Chita R. Das

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 285, Performance, Prefetch

April 27, 2013 by hgpu

A method for speeding up beam-tracing simulation using thread-level parallelization

Marjan Sikora, Ivo Mateljan

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Tags: Acoustics, Algorithms, CAD, Computer science

April 26, 2013 by hgpu

Parallel Variable Distribution Algorithm for Constrained Optimization with Nonmonotone Technique

Congying Han, Tingting Feng, Guoping He, Tiande Guo

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Tags: Algorithms, Computer science, CUDA, nVidia

April 26, 2013 by hgpu

Design and Performance Analysis of Parallel Processing of SRTP Packets

Jan Wozniak

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Tags: Computer science, Intel, OpenCL, Security

April 26, 2013 by hgpu

Accelerating Population Balance Model-based particulate process simulations via parallel computing

Anuj Varghese Prakash

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Tags: Biochemistry, Chemistry, Computer science, CUDA, Distributed computing, nVidia, nVidia GeForce GTX 280, Thesis

April 26, 2013 by hgpu

High Performance Computing with GPUs

Nikita Vakulin, Riley Shaw, Timothy Livingston

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Tags: Computer science, CUDA, Differential equations, Finite element method, nVidia, Package

April 25, 2013 by hgpu

Directive-based Approach to Heterogeneous Computing

Ruyman Reyes Castro

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Package, Python, Tesla C1060, Thesis

April 25, 2013 by hgpu

Faster Upper Body Pose Estimation and Recognition Using CUDA

Dane L. Brown, Mehrdad Ghaziasgar, James Connan

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 580

April 25, 2013 by hgpu

Reduce, Reuse, Recycle (R^3): a Design Methodology for Sparse Matrix Vector Multiplication on Reconfigurable Platforms

Kevin Townsend, Joseph Zambreno

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Tags: Computer science, CUDA, nVidia, Sparse matrix, Tesla M2090, Tesla S1070

April 23, 2013 by hgpu

Parallel Computing for Accelerated Texture Classification with Local Binary Pattern Descriptors using OpenCL

CYN Dwith, Rathna.G.N

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Tags: Algorithms, ATI, Computer science, Heterogeneous systems, OpenCL, Pattern recognition

April 23, 2013 by hgpu

Solving Wave Equations on Unstructured Geometries

Andreas Klockner, Timothy Warburton, Jan S. Hesthaven

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Tags: Computer science, Mathematical Software, Numerical Analysis, nVidia, nVidia GeForce GTX 295, OpenCL, Package, Python, Wave equation

April 23, 2013 by hgpu

GPU Scripting and Code Generation with PyCUDA

Andreas Klockner, Nicolas Pinto, Bryan Catanzaro, Yunsup Lee, Paul Ivanov, Ahmed Fasih

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Tags: Code generation, Computer science, CUDA, nVidia, OpenCL, Package, PyOpenCL, Python

April 23, 2013 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Orchestrated Scheduling and Prefetching for GPGPUs

A method for speeding up beam-tracing simulation using thread-level parallelization

Parallel Variable Distribution Algorithm for Constrained Optimization with Nonmonotone Technique

Design and Performance Analysis of Parallel Processing of SRTP Packets

Accelerating Population Balance Model-based particulate process simulations via parallel computing

High Performance Computing with GPUs

Directive-based Approach to Heterogeneous Computing

Faster Upper Body Pose Estimation and Recognition Using CUDA

Reduce, Reuse, Recycle (R^3): a Design Methodology for Sparse Matrix Vector Multiplication on Reconfigurable Platforms

Parallel Computing for Accelerated Texture Classification with Local Binary Pattern Descriptors using OpenCL

Solving Wave Equations on Unstructured Geometries

GPU Scripting and Code Generation with PyCUDA

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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