high performance computing on graphics processing units: hgpu.org

Jorge Frances Monllor, Sergio Bleda Perez, Andres Marquez Ruiz, Cristian Neipp Lopez, Sergi Gallego Rico, Beatriz Otero Calvino, Augusto Belendez Vazquez

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Tags: CUDA, FDTD, Finite-difference time-domain, Fluid dynamics, nVidia, nVidia GeForce GTX 470, Programming techniques

September 15, 2013 by hgpu

Expressed Sequence Tag Clustering using Commercial Gaming Hardware

Charl van Deventer, Willem A. Clarke, Scott Hazelhurst

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Tags: Algorithms, Bioinformatics, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package, Thesis

September 15, 2013 by hgpu

Porting to the Intel Xeon Phi: Opportunities and Challenges

C. Rosales

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Intel Phi, MPI, nVidia, Optimization, Performance

September 15, 2013 by hgpu

Quine-McCluskey algorithm on GPGPU

Vladimir Siladi, Tomas Filo

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GT 550 Ti

September 15, 2013 by hgpu

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Roger V. Hoang, Devyani Tanna, Laurence C. Jayet Bray, Sergiu M. Dascalu, Frederick C. Harris Jr.

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Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Tesla C2050

September 14, 2013 by hgpu

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

EnergyUCB-Bandit

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Parallel Computing Methods For Particle Accelerator Design

A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers

Optimal Configuration of GPU Cache Memory to Maximize the Performance

Run-time Image and Video Resizing Using CUDA-enabled GPUs

On the Performance and Energy-efficiency of Multi-core SIMD CPUs and CUDA-enabled GPUs

Hybrid Monte Carlo CT Simulation on GPU

Faster Multiple Pattern Matching System on GPU based on Bit-Parallelism

Performance analysis of SSE instructions in multi-core CPUs and GPU computing on FDTD scheme for solid and fluid vibration problems

Expressed Sequence Tag Clustering using Commercial Gaming Hardware

Porting to the Intel Xeon Phi: Opportunities and Challenges

Quine-McCluskey algorithm on GPGPU

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Recent source codes

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

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

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

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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