# Extending the ARC Information Providers to report information on GPU resources

## TL;DR

This paper discusses extending the ARC information providers to include GPU resource reporting, aiming to enhance GPGPU integration in scientific computing workflows, especially within high-energy physics analysis.

## Contribution

It introduces a GPU discovery mechanism in GRID middleware, enabling better resource management and utilization of GPGPU in scientific computing environments.

## Key findings

- Implemented GPU reporting in ARC information system.
- Facilitated GPGPU resource discovery in GRID middleware.
- Potential to improve high-throughput computing workflows.

## Abstract

General-purpose Computing on Graphics Processing Units (GPGPU) has been introduced to many areas of scientific research such as bioinformatics, cryptography, computer vision, and deep learning. However, computing models in the High-energy Physics (HEP) community are still mainly centred around traditional CPU resources. Tasks such as track fitting, particle reconstruction, and Monte Carlo simulation could benefit greatly from a high-throughput GPGPU computing model, streamlining bottlenecks in analysis turnover. This technical note describes the basis of an implementation of an integrated GPU discovery mechanism in GRID middleware to facilitate GPGPU.

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Source: https://tomesphere.com/paper/1907.09272