high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Computer science

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

Kai Zhang, Feng Chen, Xiaoning Ding, Yin Huai, Rubao Lee, Tian Luo, Kaibo Wang, Yuan Yuan, Xiaodong Zhang

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Tags: Computer science, CUDA, Data parallelism, Databases, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL

July 6, 2015 by hgpu

High Performance Approximate Sort Algorithm Using GPUs

Jun Xiao, Hao Chen, Jianhua Sun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Sorting

July 3, 2015 by hgpu

Modelling the Formation of Ordered Acentrosomal Microtubule Arrays

Alexander Ross Mace

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Tags: Biology, Computer science, Monte Carlo simulation, OpenCL, Probability, Thesis

July 3, 2015 by hgpu

Texture Cache Approximation on GPUs

Mark Sutherland, Joshua San Miguel, Natalie Enright Jerger

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 780, Performance

July 3, 2015 by hgpu

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Andrea Miele

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan Black, Security

July 1, 2015 by hgpu

Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

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Tags: Computer science, CUDA, Data mining, Deep learning, Machine learning, nVidia, Tesla K40

July 1, 2015 by hgpu

Accelerating DNA Sequence Analysis using Intel Xeon Phi

Suejb Memeti, Sabri Pllana

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Tags: Bioinformatics, Computer science, Intel Xeon Phi, OpenMP, Performance

July 1, 2015 by hgpu

The Potential of the Intel Xeon Phi for Supervised Deep Learning

Andre Viebke, Sabri Pllana

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Tags: CNN, Computer science, Deep learning, Intel Xeon Phi, Neural networks, OpenMP, Performance

July 1, 2015 by hgpu

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Amir Gholami, Judith Hill, Dhairya Malhotra, George Biros

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Tags: Algorithms, Computer science, CUDA, FFT, MPI, nVidia, OpemMP, Package, Tesla K20

June 30, 2015 by hgpu

Intra-Application Data-Communication Characterization

Imran Ashraf, Vlad-Mihai Sima, Koen Bertels

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 640

June 30, 2015 by hgpu

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Marijn F. Stollenga, Wonmin Byeon, Marcus Liwicki, Juergen Schmidhuber

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Tags: Computer science, CUDA, Deep learning, Image processing, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan X

June 26, 2015 by hgpu

Concurrent Solutions to Linear Systems using Hybrid CPU/GPU Nodes

Oluwapelumi Adenikinju, Julian Gilyard, Joshua Massey, Thomas Stitt

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Tags: Computer science, CUDA, Linear Algebra, nVidia, OpenGL, OpenMP

June 26, 2015 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

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high performance computing on graphics processing units: hgpu.org

Applications

Hetero-DB: Next Generation High-Performance Database Systems by Best Utilizing Heterogeneous Computing and Storage Resources

High Performance Approximate Sort Algorithm Using GPUs

Modelling the Formation of Ordered Acentrosomal Microtubule Arrays

Texture Cache Approximation on GPUs

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Heterogeneous Network Embedding via Deep Architectures

Accelerating DNA Sequence Analysis using Intel Xeon Phi

The Potential of the Intel Xeon Phi for Supervised Deep Learning

AccFFT: A library for distributed-memory FFT on CPU and GPU architectures

Intra-Application Data-Communication Characterization

Parallel Multi-Dimensional LSTM, With Application to Fast Biomedical Volumetric Image Segmentation

Concurrent Solutions to Linear Systems using Hybrid CPU/GPU Nodes

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

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