high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Barrier Invariants: A Shared State Abstraction for the Analysis of Data-Dependent GPU Kernels

Nathan Chong, Alastair F. Donaldson, Paul H.J. Kelly, Jeroen Ketema, Shaz Qadeer

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Tags: Algorithms, Computer science, CUDA, OpenCL, Package, Performance

August 13, 2013 by hgpu

Executing Process Networks on Heterogeneous Platforms using OpenCL

Tobias Scherer

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Tags: ATI, ATI Radeon HD 7750, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 670, nVidia Quadro K 2000 M, OpenCL, Thesis

August 13, 2013 by hgpu

Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs

A. K. Bahl, O. Baltzer, A. Rau-Chaplin, B. Varghese, A. Whiteway

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Tags: Algorithms, Computer science, CUDA, Finance, nVidia, Risk Management, Stochastic simulation, Tesla C2075, Tesla M2090

August 13, 2013 by hgpu

GPU Computing in Discrete Optimization. Part II: Survey Focused on Routing Problems

Christian Schulz, Geir Hasle, Andre R. Brodtkorb, Trond R. Hagen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

August 12, 2013 by hgpu

GPU Computing in Discrete Optimization. Part I: Introduction to the GPU

Andre R. Brodtkorb, Trond R. Hagen, Christian Schulz, Geir Hasley

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

August 12, 2013 by hgpu

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

Aman Bahl, Oliver Baltzer, Andrew Rau-Chaplin, Blesson Varghese

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Tags: Algorithms, Computational Engineering, Computer science, CUDA, Finance, Monte Carlo simulation, nVidia, Stochastic simulation, Tesla C2075

August 12, 2013 by hgpu

Molecular Dynamics Simulation of Multi-Scale Flows on GPUs

S. Mulla, S. Ivekovic, J.M. Reese

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Tags: Biology, Chemistry, CUDA, Molecular dynamics, nVidia, OpenCL, Tesla M2075

August 12, 2013 by hgpu

A Memory Efficient Algorithm for Adaptive Multidimensional Integration with Multiple GPUs

Kamesh Arumugam, Alexander Godunov, Desh Ranjan, Balsa Terzic, Mohammad Zubair

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Tags: Algorithms, Computer science, CUDA, Mathematics, MPI, nVidia, Optimization, Package, Tesla M2090

August 12, 2013 by hgpu

A Parallel Algorithm for Calculation of Large Determinants with High Accuracy for GPUs and MPI clusters

Gleb Beliakov, Yuri Matiyasevich

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, MPI, Number Theory, Numerical Analysis, nVidia, Tesla C2070

August 12, 2013 by hgpu

Heterogeneous Computing for Real-Time Stereo Matching

A. AL-Marakeby, M. Zaki

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 610 M, Stereo vision

August 10, 2013 by hgpu

Analyzing Optimization Techniques for Power Efficiency on Heterogeneous Platforms

Yash Ukidave, David Kaeli

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Tags: Algorithms, ATI, ATI Radeon HD 7770, Computer science, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, Power-efficient computing

August 10, 2013 by hgpu

PixelPie: Maximal Poisson-disk Sampling with Rasterization

Cheuk Yiu Ip, M. Adil Yalcin, David Luebke, Amitabh Varshney

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Tags: Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 580, OpenGL, Rasterization

August 10, 2013 by hgpu

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Private LLM Inference on Consumer Blackwell GPUs: A Practical Guide for Cost-Effective Local Deployment in SMEs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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high performance computing on graphics processing units: hgpu.org

Applications

Barrier Invariants: A Shared State Abstraction for the Analysis of Data-Dependent GPU Kernels

Executing Process Networks on Heterogeneous Platforms using OpenCL

Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs

GPU Computing in Discrete Optimization. Part II: Survey Focused on Routing Problems

GPU Computing in Discrete Optimization. Part I: Introduction to the GPU

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

Molecular Dynamics Simulation of Multi-Scale Flows on GPUs

A Memory Efficient Algorithm for Adaptive Multidimensional Integration with Multiple GPUs

A Parallel Algorithm for Calculation of Large Determinants with High Accuracy for GPUs and MPI clusters

Heterogeneous Computing for Real-Time Stereo Matching

Analyzing Optimization Techniques for Power Efficiency on Heterogeneous Platforms

PixelPie: Maximal Poisson-disk Sampling with Rasterization

Recent source codes

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

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

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