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Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures

Kaushik Datta, Mark Murphy, Vasily Volkov, Samuel Williams, Jonathan Carter, Leonid Oliker, David Patterson, John Shalf, Katherine Yelick

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Tags: Cell processor, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 280, Performance

December 14, 2010 by hgpu

Orders-of-magnitude performance increases in GPU-accelerated correlation of images from the International Space Station

Peter Lu, Hidekazu Oki, Catherine Frey, Gregory Chamitoff, Leroy Chiao, Edward Fincke, C. Foale, Sandra Magnus, William McArthur, Daniel Tani, Peggy Whitson, Jeffrey Williams, William Meyer, Ronald Sicker, Brion Au, Mark Christiansen, Andrew Schofield, David Weitz

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Tags: CUDA, Image processing, Image registration, nVidia, nVidia GeForce GTX 280, nVidia Quadro FX 5800, Tesla C1060

December 13, 2010 by hgpu

Fast and automatic object pose estimation for range images on the GPU

In Park, Marcel Germann, Michael Breitenstein, Hanspeter Pfister

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 280

December 13, 2010 by hgpu

New Row-grouped CSR format for storing the sparse matrices on GPU with implementation in CUDA

Tomas Oberhuber, Atsushi Suzuki, Jan Vacata

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Sparse matrix

December 13, 2010 by hgpu

Particle-in-cell Simulations with Charge-Conserving Current Deposition on Graphic Processing Units

Xianglong Kong, Michael C. Huang, Chuang Ren, Viktor K. Decyk

Tags: CUDA, nVidia, nVidia GeForce GTX 280, Particle-in-cell methods, Physics, Plasma physics

December 11, 2010 by hgpu

Shared Sampling for Real-Time Alpha Matting

Eduardo S. L. Gastal, Manuel M. Oliveira

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Tags: Computer vision, GLSL, Image processing, nVidia, nVidia GeForce GTX 280

December 4, 2010 by hgpu

Accelerating error correction in high-throughput short-read DNA sequencing data with CUDA

Haixiang Shi, B. Schmidt, Weiguo Liu, W. Muller-Wittig

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Tags: Algorithms, Computer science, CUDA, Error recovery, nVidia, nVidia GeForce GTX 280

November 27, 2010 by hgpu

Parallel reconstruction of neighbor-joining trees for large multiple sequence alignments using CUDA

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

November 27, 2010 by hgpu

A Note on Auto-tuning GEMM for GPUs

Yinan Li, Jack Dongarra, Stanimire Tomov

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 280

November 27, 2010 by hgpu

CUDA-MEME: Accelerating Motif Discovery in Biological Sequences Using CUDA-enabled Graphics Processing Units

Yongchao Liu, Bertil Schmidt, Weiguo Liu, Douglas L. Maskell

Tags: Biology, CUDA, nVidia, nVidia GeForce GTX 280, Pattern recognition

November 27, 2010 by hgpu

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Mingliang Wang, Hector Klie, Manish Parashar, Hari Sudan

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla T10P

November 27, 2010 by hgpu

The Virtual Marathon: Parallel Computing Supports Crowd Simulations

Erdal Yilmaz, Veysi Isler, Yasemin Y. Cetin

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Tags: Computer science, nVidia, nVidia GeForce GTX 280, OpenGL, Visualization

November 27, 2010 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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