high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » paper

GLoP: Enabling Massively Parallel Incident Response Through GPU Log Processing

X. Bellekens, C. Tachtatzis, R. C. Atkinson, C. Renfrew, T. Kirkham

View

Download (PDF)

Tags: CUDA, nVidia, Security, Tesla K20

April 9, 2016 by xhgpu

A Highly-Efficient Memory-Compression Scheme for GPU-Accelerated Intrusion Detection Systems

X. J. A. Bellekens, C. Tachtatzis, R. C. Atkinson, C. Renfrew, T. Kirkham

View

Download (PDF)

Tags: CUDA, nVidia, Security, Tesla K20

April 9, 2016 by xhgpu

An Exploratory Study of High Performance Graphics Application Programming Interfaces

Joseph Shiraef

View

Download (PDF)

Tags: AMD Radeon R9 290X, ATI, Computer science, DirectX, nVidia, nVidia GeForce GTX 970, OpenGL, Performance, Thesis, Vulkan

April 6, 2016 by hgpu

gpucc: an open-source GPGPU compiler

Jingyue Wu, Artem Belevich, Eli Bendersky, Mark Heffernan, Chris Leary, Jacques Pienaar, Bjarke Roune, Rob Springer, Xuetian Weng, Robert Hundt

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, LLVM, nVidia, Presentation, Tesla K40

April 6, 2016 by hgpu

Automatic test case reduction of randomly generated OpenCL kernels

Moritz Pflanzer

View

Download (PDF)

Tags: Code generation, Computer science, LLVM, nVidia, nVidia GeForce GT 630, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, nVidia Quadro K5200, OpenCL, Thesis

April 6, 2016 by hgpu

Are Very Deep Neural Networks Feasible on Mobile Devices?

S. Rallapalli, H. Qiu, A. J. Bency, S. Karthikeyan, R. Govindan, B.S.Manjunath, R. Urgaonkar

View

Download (PDF)

Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia Jetson TK1

April 6, 2016 by hgpu

GPU-accelerated stochastic predictive control of drinking water networks

Ajay K. Sampathirao, Pantelis Sopasakis, Alberto Bemporad, Panagiotis Patrinos

View

Download (PDF)

Tags: CUDA, Mathematics, nVidia, Tesla C2075

April 6, 2016 by hgpu

Implementation of the SYCL Heterogeneous Computing Library

Peter Zuzek

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, Heterogeneous systems, OpenCL, Package, SYCL, Thesis

April 3, 2016 by hgpu

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Kenichi W. Okamoto, Priyanga Amarasekare

View

Download (PDF)

Source codes

Tags: Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 690, Package

April 3, 2016 by hgpu

Classiffication-based Financial Markets Prediction using Deep Neural Networks

Matthew Dixon, Diego Klabjan, Jin Hoon Bang

View

Download (PDF)

Tags: Computer science, Deep learning, Finance, Intel Xeon Phi, Neural networks

April 3, 2016 by hgpu

Dynamic Sparse-Matrix Allocation on GPUs

James King, Thomas Gilray, Robert M. Kirby, Matthew Might

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse matrix, Tesla K20

April 3, 2016 by hgpu

Evaluating the Performance Impact of Multiple Streams on the MIC-based Heterogeneous Platform

Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Cheng Chen, Canqun Yang

View

Download (PDF)

Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Xeon Phi, Performance

April 3, 2016 by hgpu

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

GLoP: Enabling Massively Parallel Incident Response Through GPU Log Processing

A Highly-Efficient Memory-Compression Scheme for GPU-Accelerated Intrusion Detection Systems

An Exploratory Study of High Performance Graphics Application Programming Interfaces

gpucc: an open-source GPGPU compiler

Automatic test case reduction of randomly generated OpenCL kernels

Are Very Deep Neural Networks Feasible on Mobile Devices?

GPU-accelerated stochastic predictive control of drinking water networks

Implementation of the SYCL Heterogeneous Computing Library

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Classiffication-based Financial Markets Prediction using Deep Neural Networks

Dynamic Sparse-Matrix Allocation on GPUs

Evaluating the Performance Impact of Multiple Streams on the MIC-based Heterogeneous Platform

Recent source codes

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

ThunderKittens: Tile primitives for speedy kernels

NVIDIA Nemotron Parse 1.1

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

Most viewed papers (last 30 days)