high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GTX 540 M

GPU concurrency: Weak behaviours and programming assumptions

Jade Alglave, Mark Batty, Alastair F. Donaldson, Ganesh Gopalakrishnan, Jeroen Ketema, Daniel Poetzl, Tyler Sorensen, John Wickerson

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Computer science, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 540 M, nVidia GeForce GTX 660, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Tesla C2075

January 21, 2015 by hgpu

Parallelization of the Cuckoo Search using CUDA Architecture

Raka Jovanovic, Milan Tuba

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 540 M, Optimization

April 1, 2013 by hgpu

Parallel one-versus-rest SVM training on the GPU

Sander Dieleman, Aaron van den Oord, Benjamin Schrauwen

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 540 M, nVidia GeForce GTX 560 Ti, Search strategies, Tesla C1060

January 4, 2013 by hgpu

Distributed OpenCL Distributing OpenCL Platform on Network Scale

Baris Eskikaya, D Turgay Altilar

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6370 M, Computer science, Distributed computing, GPU cluster, nVidia, nVidia GeForce GT 240 M, nVidia GeForce GT 520 M, nVidia GeForce GT 525 M, nVidia GeForce GTX 540 M, nVidia GeForce GTX 555 M, OpenCL

July 15, 2012 by hgpu

Parallelization of the Local Threshold and Boolean Function Based Edge Detection Algorithm Using CUDA

Raka Jovanovic, Milan Tuba, Dana Simian

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 540 M

May 26, 2012 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

GPU concurrency: Weak behaviours and programming assumptions

Parallelization of the Cuckoo Search using CUDA Architecture

Parallel one-versus-rest SVM training on the GPU

Distributed OpenCL Distributing OpenCL Platform on Network Scale

Parallelization of the Local Threshold and Boolean Function Based Edge Detection Algorithm Using CUDA

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

Most viewed papers (last 30 days)