high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer science

Graduate Operating Systems: Project Report

James Sweet

View

Tags: AES, ATI, ATI Radeon HD 6750 M, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Operating systems, Security, Tesla M2070

January 7, 2012 by hgpu

GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement

Hartwig Anzt, Piotr Luszczek, Jack Dongarra, Vincent Heuveline

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Mixed precision, nVidia, Tesla C2070

January 6, 2012 by hgpu

Hyper neural network on OpenCL

Frantisek Sindelar

View

Download (PDF)

Tags: Algorithms, Compression, Computer science, Genetic programming, Neural networks, nVidia, nVidia Quadro NVS 140 M, OpenCL, Thesis

January 6, 2012 by hgpu

Lossless Compression of Variable-Precision Floating-Point Buffers on GPUs

Jeff Pool, Anselmo Lastra, Montek Singh

View

Download (PDF)

Tags: Compression, Computer science, Programming techniques

January 6, 2012 by hgpu

CodePy

Martin Kempf

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, nVidia, Package, Python

January 6, 2012 by hgpu

Low-power Task Scheduling for GPU Energy Reduction

Li Tang, Yiji Zhang

View

Download (PDF)

Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 210, nVidia GeForce GTX 280, nVidia GeForce GTX 570, Operating systems, Task scheduling

January 6, 2012 by hgpu

Efficient 3D reconstruction of large-scale urban environments from street-level video

David Gallup

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 285, Security, Thesis

January 6, 2012 by hgpu

A GPU Implementation of Inclusion-based Points-to Analysis

Mario Mendez-Lojo, Martin Burtscher, Keshav Pingali

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Performance, Programming techniques, Tesla C2070

January 5, 2012 by hgpu

PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

Yifeng Chen, Xiang Cui, Hong Mei

View

Download (PDF)

Tags: Code generation, Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, MPI, nVidia, Optimization, Performance, Programming techniques, Pthreads, Tesla C1060

January 5, 2012 by hgpu

Selecting the Best Tridiagonal System Solver Projected on Multi-Core CPU and GPU Platforms

Pablo Quesada-Barriuso, Julian Lamas-Rodriguez, Dora B. Heras, Montserrat Boo, Francisco Arguello

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 295, OpenMP

January 5, 2012 by hgpu

BFROST: Binary Features from Robust Orientation Segment Tests accelerated on the GPU

Jaco Cronje

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Pattern recognition, SIFT

January 5, 2012 by hgpu

Implementation of Keccak hash function in Tree hashing mode on Nvidia GPU

Guillaume Sevestre

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTS 250, nVidia Quadro FX 370 M, Optimization, Package, Security, Stream Ciphers

January 5, 2012 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Graduate Operating Systems: Project Report

GPU-Accelerated Asynchronous Error Correction for Mixed Precision Iterative Refinement

Hyper neural network on OpenCL

Lossless Compression of Variable-Precision Floating-Point Buffers on GPUs

CodePy

Low-power Task Scheduling for GPU Energy Reduction

Efficient 3D reconstruction of large-scale urban environments from street-level video

A GPU Implementation of Inclusion-based Points-to Analysis

PARRAY: A Unifying Array Representation for Heterogeneous Parallelism

Selecting the Best Tridiagonal System Solver Projected on Multi-Core CPU and GPU Platforms

BFROST: Binary Features from Robust Orientation Segment Tests accelerated on the GPU

Implementation of Keccak hash function in Tree hashing mode on Nvidia GPU

Recent source codes

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Most viewed papers (last 30 days)