high performance computing on graphics processing units: hgpu.org

Kenji Ogawa, Tatsumi Aoyama, Hiroaki Ikeda, Etsuko Itou, Masafumi Kurachi, C.-J. David Lin, Hideo Matsufuru, Hiroshi Ohki, Tetsuya Onogi, Eigo Shintani, Takeshi Yamazaki

View

Download (PDF)

Tags: CUDA, GPU cluster, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla C1060

November 8, 2011 by hgpu

Improving CUDASW++, a Parallelization of Smith-Waterman for CUDA Enabled Devices

Doug Hains, Zach Cashero, Mark Ottenberg, Wim Bohm, Sanjay Rajopadhye

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Sequence alignment, Smith-Waterman algorithm, Tesla C1060, Tesla C2050

November 5, 2011 by hgpu

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

George Bosilca, Aurelien Bouteiller, Thomas Herault, Pierre Lemarinier, Narapat Ohm Saengpatsa, Stanimire Tomov, Jack J. Dongarra

View

Download (PDF)

Tags: Computer science, Factorization, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, Performance, Tesla C1060, Tesla C2050, Tesla S1070

November 3, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Natural HPC substrate: Exploitation of mixed multicore CPU and GPUs

Seismic Wave Propagation Simulation Using Accelerated Support Operator Rupture Dynamics on Multi-GPU

A fast and robust seed flooding algorithm on GPU for Voronoi diagram generation

B-CALM: An open-source GPU-based 3D-FDTD with multi-pole dispersion for plasmonics

rCUDA: Reducing the number of GPU-based accelerators in high performance clusters

GPU-based Signal Processing Scheme for Bioinspired Optical Flow

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems in a Hybrid CPU-GPU Computing Environment

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

High performance massively parallel direct N-body simulations on large GPU clusters

The Infrared behavior of SU(3) Nf=12 gauge theory -about the existence of conformal fixed point-

Improving CUDASW++, a Parallelization of Smith-Waterman for CUDA Enabled Devices

Performance Portability of a GPU Enabled Factorization with the DAGuE Framework

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)