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Key derivation functions and their GPU implementation

Ondrej Mosnacek

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Tags: Benchmarking, Computer science, nVidia, OpenCL, Package, Security, Tesla K20, Thesis

May 22, 2015 by hgpu

Toward GPUs being mainstream in analytic processing: An initial argument using simple scan-aggregate queries

Jason Power, Yinan Li, Mark D. Hill, Jignesh M. Patel, David A. Wood

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Tags: Algorithms, AMD Radeon R7 240, ATI, ATI Radeon HD 7970, Computer science, Databases, Heterogeneous systems, OpenCL

May 22, 2015 by hgpu

Physically Based Rendering: Implementation of Path Tracer

Vinh Truong

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, OpenGL, Raytracing, Rendering, Thesis

May 20, 2015 by hgpu

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

Gordon Inggs, David B. Thomas, Wayne Luk

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Tags: AMD FirePro W5000, ATI, Computational finance, Computer science, Finance, FPGA, Heterogeneous systems, Intel Xeon Phi, nVidia, nVidia Grid K2, nVidia Quadro K4000, OpenCL, Option pricing, Performance

May 20, 2015 by hgpu

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Geoffrey Ndu, Javier Navaridas, Mikel Lujan

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Tags: Benchmarking, Computer science, FPGA, OpenCL, Package, Performance

May 19, 2015 by hgpu

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Ayman Tarakji, David Hebbeker, Lyubomir Georgiev

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Tags: AMD FirePro S10000, AMD FirePro S7000, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Tesla C2050

May 16, 2015 by hgpu

Adaptive discrete cosine transform-based image compression method on a heterogeneous system platform using Open Computing Language

Nasser Alqudami, Shin-Dug Kim

Tags: Algorithms, Compression, Heterogeneous systems, Image processing, OpenCL

May 15, 2015 by hgpu

A Survey of CPU-GPU Heterogeneous Computing Techniques

Sparsh Mittal and Jeffrey S. Vetter

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Tags: APU, cpu, CPU-GPU heterogeneous computing, CUDA, load balancing, OpenCL, workload partitioning

May 13, 2015 by sparsh0mittal

GPU Ray-Traced Collision Detection: Fine Pipeline Reorganization

Francois Lehericey, Valerie Gouranton, Bruno Arnaldi

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Tags: Algorithms, ATI, ATI Radeon HD 7990, Collision detection, Computer science, OpenCL, Raytracing

May 10, 2015 by hgpu

SparkCL: A Unified Programming Framework for Accelerators on Heterogeneous Clusters

Oren Segal, Philip Colangelo, Nasibeh Nasiri, Zhuo Qian, Martin Margala

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Tags: Computer science, GPU cluster, Heterogeneous systems, Java, OpenCL, Package

May 7, 2015 by hgpu

Activity recognition from videos with parallel hypergraph matching on GPUs

Eric Lombardi, Christian Wolf, Oya Celiktutan, Bulent Sankur

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Tags: Algorithms, Computer science, Computer vision, nVidia, nVidia GeForce GTS 450, nVidia GeForce GTX 560, nVidia GeForce GTX 580, OpenCL

May 7, 2015 by hgpu

Fireflies: New software for interactively exploring dynamical systems using GPU computing

Robert Merrison-Hort

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Tags: Computer science, Differential equations, Mathematical Software, Mathematics, nVidia, nVidia GeForce GTX 460, ODEs, OpenCL, Ordinary differential equations, Package, Python

May 7, 2015 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Key derivation functions and their GPU implementation

Toward GPUs being mainstream in analytic processing: An initial argument using simple scan-aggregate queries

Physically Based Rendering: Implementation of Path Tracer

An Efficient, Automatic Approach to High Performance Heterogeneous Computing

CHO: Towards a Benchmark Suite for OpenCL FPGA Accelerators

Efficient Resource Scheduling for Big Data Processing on Accelerator-based Heterogeneous Systems

Adaptive discrete cosine transform-based image compression method on a heterogeneous system platform using Open Computing Language

A Survey of CPU-GPU Heterogeneous Computing Techniques

GPU Ray-Traced Collision Detection: Fine Pipeline Reorganization

SparkCL: A Unified Programming Framework for Accelerators on Heterogeneous Clusters

Activity recognition from videos with parallel hypergraph matching on GPUs

Fireflies: New software for interactively exploring dynamical systems using GPU computing

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

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