Abstract
Energy efficiency and computing flexibility are some of the primary design constraints of heterogeneous computing. In this paper, we present FlashAbacus, a data-processing accelerator that self-governs heterogeneous kernel executions and data storage accesses by integrating many flash modules in lightweight multiprocessors. The proposed accelerator can simultaneously process data from different applications with diverse types of operational functions, and it allows multiple kernels to directly access flash without the assistance of a host-level file system or an I/O runtime library. We prototype FlashAbacus on a multicore-based PCIe platform that connects to FPGA-based flash controllers with a 20 nm node process. The evaluation results show that FlashAbacus can improve the bandwidth of data processing by 127%, while reducing energy consumption by 78.4%, as compared to a conventional method of heterogeneous computing.
Original language | English |
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Title of host publication | Proceedings of the 13th EuroSys Conference, EuroSys 2018 |
Publisher | Association for Computing Machinery, Inc |
ISBN (Electronic) | 9781450355841 |
DOIs | |
Publication status | Published - 2018 Apr 23 |
Event | 13th EuroSys Conference, EuroSys 2018 - Porto, Portugal Duration: 2018 Apr 23 → 2018 Apr 26 |
Publication series
Name | Proceedings of the 13th EuroSys Conference, EuroSys 2018 |
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Volume | 2018-January |
Conference
Conference | 13th EuroSys Conference, EuroSys 2018 |
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Country/Territory | Portugal |
City | Porto |
Period | 18/4/23 → 18/4/26 |
Bibliographical note
Funding Information:This research is mainly supported by NRF 2016R1C1B2015312 and MemRay grant (2015-11- 1731). This work is also supported in part by, DOE DEAC02-05CH 11231, IITP-2017-2017-0-01015, and NRF2015M3C4A7065645. The authors thank Gilles Muller for shepherding this paper. We also thank MemRay Corporation and Texas Instruments for their research sample donation and technical support. Myoungsoo jung is the corresponding author.
Publisher Copyright:
© 2018 Association for Computing Machinery.
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
- Hardware and Architecture
- Computer Networks and Communications