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Accelerating string tokenization with FPGAs for IoT data handling equipment

Kazuhiro Yamato

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Tags: Computer science, FPGA, IoT, OpenCL

December 3, 2016 by hgpu

Hardware thread reordering to boost OpenCL throughput on FPGAs

Amir Momeni, Hamed Tabkhi, Gunar Schirner, David Kaeli

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Tags: Computer science, FPGA, Hardware, OpenCL, Performance

November 30, 2016 by hgpu

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Pedro Miguel Marques Pereira

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, ATI Radeon HD 7970, Compression, Computer science, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 570 M, nVidia GeForce GTX 680, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan Black, nVidia Jetson TK1, OpenCL, OpenMP, Thesis

November 30, 2016 by hgpu

A Metric for Performance Portability

S. J. Pennycook, J. D. Sewall, V. W. Lee

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Tags: Computer science, CUDA, OpenACC, OpenCL, Performance, performance portability

November 25, 2016 by hgpu

Performance Analysis of CUDA and OpenCL By Implementation of Cryptographic Algorithms

Manas Mahapatra

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 525 M, OpenCL, Performance, Security, Thesis

November 23, 2016 by hgpu

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications

Matthew W. Moskewicz, Ali Jannesari, Kurt Keutzer

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Source codes

Tags: AMD R9 Nano, ARM, ATI, Code generation, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package

November 23, 2016 by hgpu

Processing OLTP Workloads on Hybrid CPU/GPU Systems

Mudit Bhatnagar

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Tags: Computer science, Databases, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX Titan, OpenCL, Thesis

November 22, 2016 by hgpu

Evaluation of an OpenCL-Based FPGA Platform for Particle Filter

Shunsuke Tatsumi, Masanori Hariyama, Norikazu Ikoma

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Tags: Computer science, FPGA, OpenCL, Particle filtering

November 19, 2016 by hgpu

HIPAcc: A Domain-Specific Language and Compiler for Image Processing

Richard Membarth, Oliver Reiche, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, Compilers, Computer science, CUDA, Heterogeneous systems, Image processing, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla K20

November 19, 2016 by hgpu

OpenCL-based optimizations for acceleration of object tracking on FPGAs and GPUs

Amir Momeni, Hamed Tabkhi, Gunar Schirner, David Kaeli

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Tags: Algorithms, Computer science, FPGA, Heterogeneous systems, nVidia, OpenCL, Tesla K20

November 13, 2016 by hgpu

Executing Dynamic Data Rate Actor Networks on OpenCL Platforms

Jani Boutellier, Ilkka Hautala

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Tags: ATI, ATI Radeon HD 7750, Computer science, Heterogeneous systems, OpenCL, Signal processing

November 13, 2016 by hgpu

Hadoopcl2: Motivating the design of a distributed, heterogeneous programming system with machine-learning applications

Max Grossman, Mauricio Breternitz, Vivek Sarkar

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Tags: Algorithms, Computer science, Hadoop, Heterogeneous systems, Machine learning, MapReduce, nVidia, OpenCL, Spark, Tesla M2050

November 13, 2016 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating string tokenization with FPGAs for IoT data handling equipment

Hardware thread reordering to boost OpenCL throughput on FPGAs

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

A Metric for Performance Portability

Performance Analysis of CUDA and OpenCL By Implementation of Cryptographic Algorithms

A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications

Processing OLTP Workloads on Hybrid CPU/GPU Systems

Evaluation of an OpenCL-Based FPGA Platform for Particle Filter

HIPAcc: A Domain-Specific Language and Compiler for Image Processing

OpenCL-based optimizations for acceleration of object tracking on FPGAs and GPUs

Executing Dynamic Data Rate Actor Networks on OpenCL Platforms

Hadoopcl2: Motivating the design of a distributed, heterogeneous programming system with machine-learning applications

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

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

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