HPC

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Performance and Portability Evaluation of the K-Means Algorithm on SYCL with CPU-GPU architectures

URL: https://github.com/artecs-group/k-means

Description:

This work uses the k-means algorithm to asses the performance portability of one of the most advanced implementations of the literature, He-Vialle, over different programming models (DPC++, CUDA, OpenMP) and multi-vendor CPU-GPU architectures.

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Direction Field Visualization with Python

URL: https://github.com/olutosinbanjo/direction_field

Description:

This project demonstrates the visualization of a direction field with Python using the differential equation of a falling object as a case study. The effectiveness of Heterogeneous Computing is also shown by exploring optimized libraries & added functionalities in Intel® Distribution for Python*.

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Mamba

URL: https://gitlab.com/cerl/mamba/

Description:

A library-based programming model for C, C++ and Fortran based on Managed Abstract Memory Arrays, aiming to deliver simplified and efficient usage of diverse memory systems to application developers in a performance portable way.

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Nondeterministic Flexible Parallel Dataflow Architecture Using Reconfigurable FPGA Applications

URL: I did not use Devcloud because I thought it only last for a month which is not enough to learn it; but it turn that they give 4 months and extend for 4 months; so I I am trying to extend so I can do my project on the DevCloud.

Description:

a systolic none deterministic and intercrosses communication support to make dataflow pipeline applications more reliable, more flexible for producing high-performance computing. The basic idea behind this work is to obtain a dynamic reconfigurable interconnection structure for FPGA dataflow applica

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Python Data Parallel Control (dpctl)

URL: https://github.com/IntelPython/dpctl.git

Description:

Dpctl provides Python SYCL bindings and SYCL-based Python Array API library. The dpctl simplifies building Python native extensions that use oneAPI DPC++ to implement portable data-parallel functions, as well as implements such extensions for its array library.

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Phase field solvers using SYCL for microstructure evolution

URL: https://github.com/ICME-India/MicroSim

Description:

Phase field technique is used to simulate microstructure evolution during materials processing such as 3D printing and additive manufacturing apart from traditional manufacturing techniques like welding, casting etc. These non-linear PDE solvers are compute intensive and also memory intensive.

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Reducing FPGA Memory Footprint of Stencil Codes through Automatic Extraction of Memory Patterns

URL: https://github.com/robertszafa/sycl-kernels-mem-reduced

Description:

A novel algorithm to aggressively reduce on-chip block RAM (BRAM) and off-chip DRAM utilisation of stencil codes running on FPGAs. The algorithm extracts memory accesses from computational pipelines and removes all redundant intermediate arrays, including those used for stencil buffering.

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eXTreme fine-grAined concurrent taSKing framework

URL: https://gitlab.com/pnookala/llvm-openmp.git

Description:

XTASK enables extreme fine-grained parallelism across modern many-core architectures with hundreds of cores by implementing a novel lock-less multiple producer multiple consumer, out-of-order queuing mechanism for managing parallel tasks.

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PLSSVM - Parallel Least Squares Support Vector Machine

URL: https://github.com/SC-SGS/PLSSVM

Description:

We propose the PLSSVM library, which efficiently brings SVMs to massively parallel accelerators. It implements the basic functionality of the most widely used SVM library, LIBSVM, and can target different hardware from various vendors by using our backends: OpenMP, CUDA, HIP, OpenCL, and SYCL.

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Gavin AI

URL: https://github.com/Gavin-Development

Description:

Gavin AI is a project, created by Scot_Survivor (Joshua Shiells) & ShmarvDogg, which aims to have Englsih human like conversations through the use of AI and ML. Gavin works on the Transformer architecture however, Performer & FNet architectures are being investigated for better scaling.

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Distributed k-Nearest Neighbors using Locality-Sensitive Hashing and SYCL

URL: https://github.com/SC-SGS/Distributed_GPU_LSH_using_SYCL

Description:

In the age of AI, algorithms must efficiently cope with vast data sets. We propose a performance-portable implementation of Locality-Sensitive Hashing (LSH), an approximate k-nearest neighbors algorithm, using different SYCL implementations—ComputeCpp, hipSYCL, DPC++—supporting multiple GPUs.

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