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Publication Information

Title ESnet / JLab FPGA Accelerated Transport
Authors Michael Goodrich, Carl Timmer, Vardan Gyurjyan, David Lawrence, William Heyes, Yatish Kumar, Stacey Sheldon
JLAB number JLAB-CST-22-3718
LANL number (None)
Other number DOE/OR/23177-5610
Document Type(s) (Journal Article) 
Associated with EIC: No
Supported by Jefferson Lab LDRD Funding: No
Funding Source: Advanced Scientific Computing Research (ASCR)

Compiled for IEEE Transactions on Nuclear Science
Volume 70
Issue 6
Page(s) 1096-1101
Publication 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, core compute hosts, and CPUs within a host. The LB effectively provides seamless integration of edge / core computing to support direct experimental data processing for immediate use by JLab science programs and others such as the EIC as well as data centers of the future requiring high throughput and low latency for both hot and cooled data for both running experiment data acquisition systems and data center use cases.
Experiment Numbers: other
Group: Scientific Computing
Document: pdf
Accepted Manuscript: FINAL VERSION.pdf
Supporting Documents:
Supporting Datasets: