Deliver uncompromised performance for diverse workloads across multiple architectures.
URL: https://github.com/artecs-group/k-means
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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URL: https://build.opensuse.org/package/show/home:cabelo:intel/intel-oneapi-onevpl
This project is an initiative to provide the oneAPI Video Processing Library packages for openSUSE Linux distributions.
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URL: https://github.com/olutosinbanjo/direction_field
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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URL: https://www.kaggle.com/code/rishirajacharya/oneapi-modin-gives-pandas-wings
An element of the oneAPI AI Analytics toolbox is Intel® Distribution of Modin. With little any work, you can scale data analytics and speed up your current Pandas code. Learn how to run the same Pandas code 10, 20, or 30 times quicker.
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Project on making a system using oneAPI Deep Neural Network Library to check and assess the answer sheets of thousands of candidates for various tests for organizations using ML/DL techniques Dataset: with the help of the MNIST dataset
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URL: https://github.com/andreicozma1/oneAPI-viz
This project explores the possibilities of using attention-based transformer models to aid in tasks related to data visualization and interpretation, through the use of various Intel oneAPI toolkits such as the DNN library, oneAPI AI Kit, as well as oneAPI Render Kit.
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URL: https://github.com/menotti/Kalman-Filter-for-Beginners/
The objective of this project is to accelerate implementations of the Kalman filter for various purposes, including the calculation of drone attitude.
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URL: https://github.com/robertszafa/elastic-sycl-hls
Current HLS tools fail to synthesise efficient architectures for irregular codes because they rely on static scheduling. Elastic dataflow techniques enable circuits to be scheduled dynamically and achieve a higher performance in accelerating irregular codes.
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URL: https://github.com/QuanticTechnovations/OneAPI_RiskAnalyzer
Significant business decisions is taken based on the outcome predicted by the ML model. Users get benefit from an unbiased, statistically sound and rigorous re-validation of the prediction’s accuracy from an independent source. That is what the Predictive Risk Analyzer tool from Quantic aims to go.
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URL: https://github.com/seelabutk/substrate
Substrate is a tool that allows you to automate the process of deploying visualization tools to different computing environments.
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URL: https://github.com/branson2015/FractalMarcher
Fractal rendering utilizing Ray Marching
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URL: https://github.com/blackout-ai/Face_Aging_Concept_Drift
This concept drift project is run on video and image datasets such that we can calculate an overall precision and standard error. The concept drift detection technique finds True positives and False negatives using real and virtual drift detection.
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URL: https://github.com/seqan/seqan3
This project targets specifically the acceleration of the pairwise alignment algorithms and pattern matching algorithms contained in the SeqAn library.
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URL: https://github.com/IntelPython/dpctl.git
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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URL: https://gitlab.com/VileLasagna/toyBrot
toyBrot is a raymarching fractal generator that is used both as a simple benchmarking tool and a study tool for parallelisation. The code is is implemented with over 10 different technologies, including Intel TBB, ISPC and SYCL (with support for oneAPI)
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URL: https://github.com/beehive-lab/TornadoVM
TornadoVM is an open-source software technology that automatically accelerates Java programs on multi-core CPUs, GPUs, and FPGAs.
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URL: https://github.com/cabelo/VirConI
Personal Protective Equipment (PPE) Detector
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URL: https://github.com/ICME-India/MicroSim
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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URL: https://github.com/rachelselinar/DREAMPlaceFPGA
This work aims to accelerate the different stages involved in FPGA placement - global placement, legalization and detailed placement, using the Pytorch deep-learning toolkit. Placement in the FPGA design flow determines the physical locations of all the heterogeneous instances in the design.
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URL: https://github.com/oneTBB-UMA/vivid-oneAPI
Heterogeneous image processing using some of the most popular features of oneAPI.
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