EngineCL: Usability and Performance in Heterogeneous Computing

Author:

Nozal Raúl,Bosque Jose Luis,Beivide Ramon

Funder

Spanish Ministry of Education

Spanish Science and Technology Commission

European HiPEAC Network of Excellence

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference48 articles.

1. Heterogeneous computing: Here to stay;Zahran;Queue,2016

2. Scaling deep learning workloads: NVIDIA DGX-1/pascal and intel knights landing;Gawande,2017

3. The Microarchitecture of Intel, AMD and VIA CPUs;Fog,2018

4. Heterogeneous Computing with OpenCL - Revised OpenCL;Gaster,2013

5. B. Pérez, et al. Simplifying programming and load balancing of data parallel applications on heterogeneous systems, in: Proc. of the 9th Workshop on General Purpose Processing using GPU (2016).

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2. POAS: a framework for exploiting accelerator level parallelism in heterogeneous environments;The Journal of Supercomputing;2024-03-25

3. Task‐based preemptive scheduling on FPGAs leveraging partial reconfiguration;Concurrency and Computation: Practice and Experience;2023-07-19

4. A machine learning-based resource-efficient task scheduler for heterogeneous computer systems;The Journal of Supercomputing;2023-04-20

5. Mashing load balancing algorithm to boost hybrid kernels in molecular dynamics simulations;The Journal of Supercomputing;2022-07-21

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