Use this URL to cite or link to this record in EThOS:
Title: A framework for managing shared accelerators in heterogeneous environments
Author: O'Neill, Eoghan Martin
ISNI:       0000 0004 5992 6609
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2015
Availability of Full Text:
Full text unavailable from EThOS.
Please contact the current institution’s library for further details.
Heterogeneous processing technologies provide opportunities for new levels of flexibility and performance in applications. Current utilisation of such technologies has focused on HPC workloads and often couples applications to specific device targets through low level code. While this approach can produce optimal performance for specialised applications on a fixed hardware platform, it requires significant expertise to code and is not portable. This work presents an approach that reduces development overheads for high-level application developers and provides a framework to allow applications to dynamically target heterogeneous devices. A task based approach to application development is presented that decouples high-level code from device specific logic and also removes any need to manually manage devices from within applications. The SHEPARD framework facilitates this through a central repository of device specific implementations, and couples these with execution time estimates to effectively allocate tasks among shared heterogeneous processors. The approach presented in this work is applied to various In-Memory Database scenarios including analytic workloads. Experiments show how a single task call can enable applications to execute code on multiple devices, and managing such tasks among a limited set of devices can allow multiple user workloads to share resources effectively, while improving workload performance.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available