HPC

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MetaCL-SNAP

URL: https://github.com/vtsynergy/MetaCL-SNAP

Description:

SNAP https://github.com/UoB-HPC/SNAP-OpenCL , serves as a proxy application to model modern discrete ordinates neutral particle transport application. In this project we leverage the existing OpenCL implementation of SNAP and evaluate the performance and productivity of MetaCL version of SNAP.

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gene sequence de-redundancy

URL: https://gitee.com/ju_zhen/nGIA

Description:

A novel Greedy Incremental Alignment-based algorithm called nGIA was proposed for sequence clustering with high efficiency and precision. The nGIA consists of a pre-filter, a modified short word filter, a new data packing strategy, a modified greedy incremental method, and is parallelized via GPU.

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TAU Performance System

URL: https://github.com/UO-OACISS/tau2

Description:

The TAU Performance System® supports profiling and tracing of programs written using the Intel OneAPI. Intel OneAPI provides two interfaces for programming - OpenCL and DPC++/SYCL for CPUs and GPUs. TAU supports both - the OpenCL profiling interface and Intel Level Zero API to observe performance.

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Migrating and Tuning a CUDA-based stencil computation to DPC++ using OneAPI

URL: https://github.com/cs2isenaicimatec/OneAPI-solving-stencil-migration

Description:

We propose the tuning and migration of a CUDA-based RTM to a DPC++ application by applying DPC++ Compatibility Tool. We aim to demonstrate the versatility of OneAPI to build unified code capable of being executed in different processing units such as CPUs and GPUs with low implementation cost.

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Spatter

URL: https://github.com/hpcgarage/spatter

Description:

Spatter is a new benchmark tool for assessing memory system architectures in the context of a specific category of indexed accesses known as gather and scatter. OneAPI and DevCloud are used to develop support for a OneAPI backend for Spatter that can be targeted to Intel FPGAs.

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Accelerate The “Stable” Three-Way QuickSort Performance Leveraging The Modern Nvidia GPGPUs

URL: https://github.com/arthurratz/parallel_stable_sort_nvptx64

Description:

Another alternative of the classical “stable” three-way quicksort performance optimization using Nvidia CUDA Development Toolkit, OpenMP 4.5/5.0 and Intel’s Open-Source Clang/LLVM compiler distribution.

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Boosting epistasis detection on Intel CPU+GPU systems

URL: https://github.com/hiperbio/cross-dpc-episdet

Description:

This work focuses on exploring the architecture of Intel CPUs and Integrated Graphics and their heterogeneous computing potential to boost performance and energy-efficiency of epistasis detection. This will be achieved making use of OpenCL, Data Parallel C++ and OpenMP programming models.

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Efficiency and productivity for decision-making on mobile SoCs

URL: https://bitbucket.org/corbera/vi-mdp/src/oneAPI/

Description:

Markov decision processes provide a formal framework for a computer to make decisions autonomously and intelligently when the effects of its actions are not deterministic. To solve this computationally complex problem, we experiment with scheduling on a low-power heterogeneous CPU+GPU SoC platform.

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A Parallel Max-Miner Algorithm For An Efficient Association Rules Learning (ARL) And Knowledge Mining Using The Intel® oneAPI Toolkit

URL: https://github.com/arthurratz/intel_max_miner_oneapi

Description:

This project demonstrates the using of the Intel® oneAPI library to deliver a modern code in Data Parallel C++, implementing a Parallel Max-Miner algorithm to optimize the performance of the association rules learning (ARL) process

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