high performance computing on graphics processing units: hgpu.org

hgpu.org » Hashing

Multi Agent Navigation on the GPU

Avi Bleiweiss

View

Tags: Artificial intelligence, Computer science, CUDA, Games, Hashing, nVidia, nVidia GeForce GTX 280, Search strategies

March 11, 2011 by hgpu

Fast Implementation of Two Hash Algorithms on nVidia CUDA GPU

Gorka Lerchundi Osa

View

Download (PDF)

Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 9400 GT, Thesis

February 24, 2011 by hgpu

Low latency photon mapping using block hashing

Vincent C. H. Ma, Michael D. Mccool

View

Download (PDF)

Tags: Algorithms, Computer science, Hashing, Rendering

January 7, 2011 by hgpu

Perfect spatial hashing

Sylvain Lefebvre, Hugues Hoppe

View

Download (PDF)

Tags: Computer science, DirectX, Hashing, HLSL, nVidia, nVidia GeForce 7800 GTX

December 4, 2010 by hgpu

Using Graphics Processors for Parallelizing Hash-based Data Carving

Sylvain Collange, Yoginder Dandass, Marc Daumas, David Defour

View

Download (PDF)

Tags: Computer science, Data recovery, Hashing, nVidia, nVidia GeForce 8500 GT, nVidia GeForce 8600 M GT

November 13, 2010 by hgpu

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Samer Al-Kiswany, Abdullah Gharaibeh, Elizeu Santos-Neto, George Yuan, Matei Ripeanu

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 9800 GTX, Package, Storage system

November 6, 2010 by hgpu

On GPU’s viability as a middleware accelerator

Samer A. Kiswany, Abdullah Gharaibeh, Elizeu S. Neto, Matei Ripeanu

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 8800 GTX, Package, Storage system

October 27, 2010 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

Multi Agent Navigation on the GPU

Fast Implementation of Two Hash Algorithms on nVidia CUDA GPU

Low latency photon mapping using block hashing

Perfect spatial hashing

Using Graphics Processors for Parallelizing Hash-based Data Carving

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

On GPU’s viability as a middleware accelerator

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)