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A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Jude-Thaddeus Ojiaku

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Tags: ATI, ATI Radeon HD 7750, ATI Radeon HD 7970, Bioinformatics, Computer science, Graph layout, Heterogeneous systems, nVidia, nVidia GefForce GTX 650, nVidia GefForce GTX 680, OpenCL, Thesis

October 29, 2017 by hgpu

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

Efficient Video Compression via Content-Adaptive Super-Resolution

CUDA Modular Polynomial (CUMODP) Library

Parallel Arbitrary-precision Integer Arithmetic

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

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high performance computing on graphics processing units: hgpu.org

A Study of Time and Energy Efficient Algorithms for Parallel and Heterogeneous Computing

Recent source codes

Easy and Efficient Transformer: Scalable Inference Solution For large NLP mode

Ripple: Simplified Large-Scale Computation on Heterogeneous Architectures with Polymorphic Data Layout

CrypTen: a framework for Privacy Preserving Machine Learning built on PyTorch

SLATE: Software for Linear Algebra Targeting Exascale project

MG-CFD OP2

Megatron

pharos: performance monitoring instrumentation for multi-FPGA systems

Efficient Video Compression via Content-Adaptive Super-Resolution

CUDA Modular Polynomial (CUMODP) Library

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

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Featured events

9th International Workshop on OpenCL and SYCL, 2021

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020