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Graph Analysis with High-Performance Computing

Bruce Hendrickson, Jonathan W. Berry

Tags: Computer science, Graph theory, Networks, Performance

January 20, 2011 by hgpu

TEDI: efficient shortest path query answering on graphs

Fang Wei

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Tags: Algorithms, Computer science, Networks, Path problems, Search

January 20, 2011 by hgpu

Practical and Robust Stenciled Shadow Volumes for Hardware-Accelerated Rendering

Cass Everitt, Mark J. Kilgard

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Tags: Computer science, Graphics, nVidia, nVidia GeForce 3, nVidia GeForce 4, OpenGL, Rendering

January 20, 2011 by hgpu

Implicit Parallel Time Integrators

Andrew Christlieb, Benjamin Ong

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Tags: Algorithms, Computer science, Programming techniques

January 19, 2011 by hgpu

Introduction to the Report “Interlanguages and Synchronic Models of Computation.”

Alexander Victor Berka

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Tags: Computer science, High-level Languages, Programming Languages

January 19, 2011 by hgpu

Space and the Synchronic A-Ram

Alex V Berka

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Tags: Computer science, High-level Languages, Programming Languages

January 19, 2011 by hgpu

Interlanguages and synchronic models of computation

Alexander Victor Berka

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Tags: Computer science, FPGA, High-level Languages, Programming Languages

January 19, 2011 by hgpu

Relational query coprocessing on graphics processors

Bingsheng He, Mian Lu, Ke Yang, Rui Fang, Naga K. Govindaraju, Qiong Luo, Pedro V. Sander

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Source codes

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce 8800 GTX, Package, Performance

January 19, 2011 by hgpu

Secure 3D graphics for virtual machines

Christopher Smowton

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Tags: Computer science, DirectX, OpenGL, Virtualization

January 18, 2011 by hgpu

Message passing for GPGPU clusters: CudaMPI

Orion S. Lawlor

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Source codes

Tags: Computer science, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 280, OpenMPI, Package

January 18, 2011 by hgpu

A novel approach for implementing Steganography with computing power obtained by combining Cuda and Matlab

Samir B. Patel, Shrikant N. Pradhan, Saumitra U. Ambegaokar

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Tags: Computer science, CUDA, nVidia, Security

January 18, 2011 by hgpu

A Multi-Stage CUDA Kernel for Floyd-Warshall

Ben Lund, Justin W Smith

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Tags: Computer science, CUDA, nVidia, Optimization, Performance, Programming techniques, Tesla C1060

January 18, 2011 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

See all packages

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high performance computing on graphics processing units: hgpu.org

Graph Analysis with High-Performance Computing

TEDI: efficient shortest path query answering on graphs

Practical and Robust Stenciled Shadow Volumes for Hardware-Accelerated Rendering

Implicit Parallel Time Integrators

Introduction to the Report “Interlanguages and Synchronic Models of Computation.”

Space and the Synchronic A-Ram

Interlanguages and synchronic models of computation

Relational query coprocessing on graphics processors

Secure 3D graphics for virtual machines

Message passing for GPGPU clusters: CudaMPI

A novel approach for implementing Steganography with computing power obtained by combining Cuda and Matlab

A Multi-Stage CUDA Kernel for Floyd-Warshall

Recent source codes

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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