high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

An approach for the effective utilization of GP-GPUs in parallel combined simulation

David W. Bauer, Matthew McMahon, Ernest H. Page

Tags: Computer science, Heterogeneous systems, Partial differential equations, PDEs, Performance

March 21, 2011 by hgpu

Joint Forces: From Multithreaded Programming to GPU Computing

Frank Feinbube, Peter Troger, Andreas Polze

Tags: Computer science, Optimization, Performance

March 20, 2011 by hgpu

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

J. Myre, S. D. C. Walsh, D. Lilja, M. O. Saar

Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, OpenMP, Performance

March 17, 2011 by hgpu

Implementing the Himeno benchmark with CUDA on GPU clusters

Everett H. Phillips, Massimiliano Fatica

Tags: Benchmarking, Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla C1060

March 16, 2011 by hgpu

Patterns of Inefficient Performance Behavior in GPU Applications

Dominic Eschweiler, Daniel Becker, Felix Wolf

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance, Tesla T10

March 16, 2011 by hgpu

General-purpose molecular dynamics simulations on GPU-based clusters

Christian R. Trott, Lars Winterfeld, Paul S. Crozier

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Source codes

Tags: Computational Physics, Condensed matter, CUDA, GPU cluster, Materials Science, Molecular dynamics, MPI, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Performance, Physics, Tesla C1060, Tesla S1070

March 8, 2011 by hgpu

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Phuong Hoai Ha, Philippas Tsigas, Otto J. Anshus

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce 8800 GTX, Performance, Programming techniques

March 7, 2011 by hgpu

Performance study of mapping irregular computations on GPUs

Steven Solomon, Parimala Thulasiraman

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Performance, Presentation

March 6, 2011 by hgpu

Tuned and asynchronous stencil kernels for CPU/GPU systems (thesis)

Sundaresan Venkatasubramanian

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 570, Performance, Tesla C1060, Tesla C870, Thesis

March 6, 2011 by hgpu

Speculative Execution on Multi-GPU Systems

Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce 9800 GX2, Optimization, Performance, Tesla S870

March 6, 2011 by hgpu

Task management for irregular-parallel workloads on the GPU

Stanley Tzeng, Anjul Patney, John D. Owens

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Optimization, Performance, Presentation, Task scheduling

March 6, 2011 by hgpu

Dynamic load balancing on single- and multi-GPU systems

Long Chen, Oreste Villa, Sriram Krishnamoorthy, Guang R. Gao

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Task scheduling, Tesla C1060

March 6, 2011 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

See all packages

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high performance computing on graphics processing units: hgpu.org

An approach for the effective utilization of GP-GPUs in parallel combined simulation

Joint Forces: From Multithreaded Programming to GPU Computing

Performance analysis of single-phase, multiphase, and multicomponent lattice-Boltzmann fluid flow simulations on GPU clusters

Implementing the Himeno benchmark with CUDA on GPU clusters

Patterns of Inefficient Performance Behavior in GPU Applications

General-purpose molecular dynamics simulations on GPU-based clusters

Non-blocking programming on multi-core graphics processors: (extended asbtract)

Performance study of mapping irregular computations on GPUs

Tuned and asynchronous stencil kernels for CPU/GPU systems (thesis)

Speculative Execution on Multi-GPU Systems

Task management for irregular-parallel workloads on the GPU

Dynamic load balancing on single- and multi-GPU systems

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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