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Publication Information
Title ESnet / JLab FPGA Accelerated Transport
Abstract To increase the science rate for high data rates/volumes, Thomas Jefferson National Accelerator Facility (JLab) has partnered with Energy Sciences Network (ESnet) to define an edge to data center traffic shaping / steering transport capability featuring data event aware network shaping and forwarding. The keystone of this ESnet+JLab FPGA Accelerated Transport (EJFAT) is the joint development of an AI/ML directed dynamic compute work Load Balancer (LB) of UDP streamed data. The LB is a suite consisting of a Field Programmable Gate Array (FPGA) executing the dynamically configurable, low fixed latency LB data plane featuring real-time packet redirection and high throughput, and a control plane running on the FPGA host computer that monitors network and compute farm telemetry in order to make dynamic AI/ML guided decisions for destination compute host redirection / load balancing and destination resource provisioning. The LB provides for three-tier horizontal scaling across LB suites, c
Author(s) Michael Goodrich, Carl Timmer, Vardan Gyurjyan, David Lawrence, Graham Heyes, Yatish Kumar, Stacey Sheldon
Publication Date June 2023
Document Type Journal Article
Primary Institution Thomas Jefferson National Accelerator Facility, Newport News
Affiliation Comp Sci&Tech (CST) Div / Scientific Computing / Scientific Computing
Funding Source Advanced Scientific Computing Research (ASCR)
Proprietary? No
This publication conveys Technical Science Results
Document Numbers
JLAB Number: JLAB-CST-22-3718 OSTI Number: 1998073
LANL Number: Other Number: DOE/OR/23177-5610
Associated with an experiment No
Associated with EIC No
Supported by Jefferson Lab LDRD Funding No
Journal Article
Journal Name IEEE Transactions on Nuclear Science
Refereed Yes
Volume 70
Issue 6
Page(s) 1096-1101
Attachments/Datasets/DOI Link
Document(s)
CD#77_goodrich.pdf (STI Document)
FINAL VERSION.pdf (Accepted Manuscript)
DOI Link
Dataset(s) (none)
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