Enabling GPU Support for the COMPSs-Mobile Framework

Using the GPUs embedded in mobile devices allows for increasing the performance of the applications running on them while reducing the energy consumption of their execution. This article presents a task-based solution for adaptative, collaborative heterogeneous computing on mobile cloud environments. To implement our proposal, we extend the COMPSs-Mobile framework – an implementation of the COMPSs programming model for building mobile applications that offload part of the computation to the Cloud – to support offloading computation to GPUs through OpenCL. To evaluate our solution, we subject the prototype to three benchmark applications representing different application patterns.This work is partially supported by the Joint-Laboratory on Extreme Scale Computing (JLESC), by the European Union through the Horizon 2020 research and innovation programme under contract 687584 (TANGO Project), by the Spanish Goverment (TIN2015-65316-P, BES-2013-067167, EEBB-2016-11272, SEV-2011-00067) and the Generalitat de Catalunya (2014-SGR-1051).Peer ReviewedPostprint (author's final draft

funcX: A Federated Function Serving Fabric for Science

Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approaches must enable computation to be mobile, so that, for example, it can occur near data, be triggered by events (e.g., arrival of new data), be offloaded to specialized accelerators, or run remotely where resources are available. They also require new design approaches in which monolithic applications can be decomposed into smaller components, that may in turn be executed separately and on the most suitable resources. To address these needs we present funcX---a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. funcX's endpoint software can transform existing clouds, clusters, and supercomputers into function serving systems, while funcX's cloud-hosted service provides transparent, secure, and reliable function execution across a federated ecosystem of endpoints. We motivate the need for funcX with several scientific case studies, present our prototype design and implementation, show optimizations that deliver throughput in excess of 1 million functions per second, and demonstrate, via experiments on two supercomputers, that funcX can scale to more than more than 130000 concurrent workers.Comment: Accepted to ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC 2020). arXiv admin note: substantial text overlap with arXiv:1908.0490