The topic is about implementation of oneAPI analytics toolkit in Medical Science.We will be exploring single cell data (eg:- scRNA sequence). We will be porting Clustergrammer2 to AI analytics toolkit. Clustergrammer2 produces highly interactive visualizations that enable intuitive exploration of high-dimensional data and has several optional biology-specific features (e.g. enrichment analysis; see Biology-Specific Features) to facilitate the exploration of gene-level biological data. It ...

Level-Zero is a close to bare-metal API for programming heterogeneous architectures, and it is shipped as part of Intel oneAPI. Additionally, it can be used as a standalone API. This article shows the basic architecture, what is used for, and an example for dispatching matrix multiplication on the Intel HD Graphics with SPIR-V.

Utilize well-known frameworks that are Intel-optimized, like as TensorFlow and PyTorch, to make the most of the Intel architecture's full potential and achieve great performance for both training and inference.

Overview Benefits The Role of a oneAPI Innovator How to Apply Become a oneAPI Innovator

Submitted a pull request at one API Src .It was accepted accordingly.

In this article, we are going to discuss about SYCL, regarding “What it’s about”, “How to implement” and other interesting topics, please give it a read and explore!

oneAPI is an open, cross-industry, standards-based, unified, multiarchitecture, multi-vendor programming model that delivers a common developer experience across accelerator architectures — for faster application performance, more productivity, and greater innovation. The oneAPI initiative encourages collaboration on the oneAPI specification and compatible oneAPI implementations across the ecosystem. In this article, we are going to learn how to use oneAPI using Intel Dev Cloud

In this series, I will try to cover the following parts: Part 1 : So Far So Good - What I have learnt about Data Parallelism and Thread Parallelism Part 2: Efficiently Splitting Instances of Input Data Across Kernels in DPC++ a. Mapping a 1-dimensional array to an Heterogeneous processor - Sequential versus Thread Parallel  b. Mapping a 1-dimensional array to an Heterogeneous processor - Data Parallel C++

Already, there are multiple informative articles written about the oneAPI programming model; this article is different as it points out the key concepts on which the oneAPI programming model is built on and for - cross-industry, open specifications, cross-architecture, unified framework, data parallel c++, heterogeneous systems, high performance and data centric.

Adding Intel oneAPI compilers and toolkits to the automated workflows for your open-source project is easier than you might think.

Introduction

Arhat is a cross-platform deep learning framework that converts neural network descriptions into lean standalone executable code. Arhat has been designed for deployment of deep learning inference workflows in the cloud and on the edge.

Arhat is a vendor-agnostic tool supporting multiple target platforms. Unlike the conventional deep learning frameworks, Arhat translates neural network descriptions directly into platform-specific executable code. This code inter...

Analysis of large volumes of legal texts represents a common task in the practice of law firms. Handling this task may require enormous investment of time and effort, therefore significant attention is being paid to automate it using the intelligent software solutions. In this post we describe the early results of our project aiming at prototyping a transformer-based NLP solution for analysis of large volumes of legal texts.

Calling all developers: Join a worldwide open source developer network as we come together during the month of October for a fun-filled 31 days of “Hack or Treat!”