Original paper Layer2/3 Services, Full Lifecycle, Multi-Domain, Multi-Resource, Interactive, End-to-End SENSE Team The Software-defined network for End-to-end Networked Science at Exascale (SENSE) research project is building intelligent network services to accelerate scientific discovery in the era of big data driven by Exascale, cloud computing, machine learning and artificial intelligence. SENSE includes a model-based orchestration system which operates between the SDN layer controlling the individual networks/end-sites, and science workflow agents/middleware. In
Super Computing 2019
October 11, 2020
FPGA-accelerated Machine Learning Inference for LHC Trigger and Computing at SC 19
Philip Harris∗1 and Javier Duarte†21Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 2Department of Physics, University of California San Diego, La Jolla, CA November 18, 2019 Original paper Abstract UCSD and MIT will lead a group of collaborators demonstrating real-time FPGA-accelerated machine learning inference. Machine learning is used in many facets of LHC data processing including the recon- struction of energy deposited by particles in the detector. The training
October 11, 2020
SC19 Network Research Exhibition NRE-022 Toward Unified Resource Discovery and Programming in Multi-Domain Networks
Submitted on behalf of the team by: Harvey Newman, Caltech, newman@hep.caltech.edu, Qiao Xiang and Jensen Zhang, Yale University, {qiao.xiang, jingxuang.zhang}@yale.edu Original NRE-022 Paper Abstract The Yale, IBM, ESNet and Caltech team will demonstrate a novel, unified multi-domain resource discovery and programming system for data-intensive collaborative sciences. Specifically, this system provides three key components: (1) a fine-grained, accurate, highly-efficient multi-domain multi-resource discovery framework (a substantial extension of the team’s SC’18 Mercator
September 8, 2020
NRE-19: SC19 Network Research Exhibition: Caltech Booth 543 Demonstrations Hosting NRE-13, NRE-19, NRE-20, NRE-22, NRE-23, NRE-24, NRE-35
Global Petascale to Exascale Workflows for Data Intensive Science Acceleratedby Next Generation Programmable SDN Architectures and Machine Learning ApplicationsSubmitted on behalf of the teams by: Harvey Newman, Caltech, newman@hep.caltech.edu: We will demonstrate several of the latest major advances in software defined and Terabit/sec networks, intelligent global operations and monitoring systems, workflow optimization methodologies with real-time analytics, and state of the art long distance data transfer methods and tools and server designs, to
August 11, 2020
Industry
Laboratory, Network & Technology Industry Partners Caltech – www.caltech.edu ESnet – www.es.net CENIC – www.cenic.org Pacific Wave – www.pacificwave.net AmLight – www.amlight.net SCinet – sc18.supercomputing.org/experience/scinet/ Ciena – www.ciena.com USC – www.usc.edu Starlight – www.startap.net/starlight/ iCAIR/Northwestern – www.icair.org MREN – www.mren.org Internet2 – www.internet2.edu Northeastern – www.northeastern.edu Yale – www.yale.edu Colorado State – www.colostate.edu Fermilab – www.fnal.gov CERN – www.cern.ch TIFR – www.tifr.res.in UCLA – www.ucla.edu KISTI – http://www.kisti.re.kr/eng/ Lawrence Berkeley Nat’l Lab – http://www.lbl.gov Michigan – https://umich.edu/ RNP – www.rnp.br ANSP – www.ansp.br UNESP – www.unesp.br/international/ REUNA – www.reuna.cl/ SURFnet – https://www.surf.nl/en/homepage CenturyLink – www.centurylink.com 2CRSI – www.2crsi.com Arista
August 11, 2020
Research Organizations
About Caltech: With an outstanding faculty that has been honored with 32 Nobel prizes and 66 National Medals of Science and Technology, and such off-campus facilities as the Jet Propulsion Laboratory, Palomar Observatory and the W. M. Keck Observatory, the California Institute of Technology is one of the world’s major research centers and a premier institution of learning. The Institute conducts instruction in science and engineering for a student body of
July 10, 2020
PhEDEx
PhEDEx is the data-placement management tool for the CMS experiment at the LHC. It manages the scheduling of all large-scale WAN transfers in CMS, ensuring reliable delivery of the data. It consists of several components: an Oracle database, hosted at CERN a website and data-service, which users (humans or machine) use to interact with and control PhEDEx a set of central agents that deal with routing, request-management, bookkeeping and other
July 10, 2020
OpenDaylight
OpenDaylight – Addressing a yet unsolved issue in LHCONE, namely the efficiency in interconnecting multiple network domains over more than one connection, Caltech is investigating and has made significant progress in developing the use of north bound interfaces to OpenDaylight SDN contoller for efficiently managing multipath networks. The software has been released under OpenSource license and is available on the github: https://pypi.python.org/pypi/python-odl/ Caltech first started working on the OpenFlow Link-layer MultiPath Switching
July 10, 2020
MonALISA
MonALISA, stands for Monitoring Agents using a Large Integrated Services Architecture, has been developed by Caltech and its partners with the support of the U.S. CMS software and computing program. The framework is based on Dynamic Distributed Service Architecture and is able to provide complete monitoring, control and global optimization services for complex systems. The MonALISA system is designed as an ensemble of autonomous multi-threaded, self-describing agent-based subsystems which are
July 10, 2020
FDT
One of the key advances in this demonstration was Fast Data Transport (FDT; https://fast-data-transfer.github.io/), an open source Java application developed by the Caltech team in close collaboration with the Polytehnica Bucharest team. FDT runs on all major platforms and uses the NIO libraries to achieve stable disk reads and writes coordinated with smooth data flow across long-range networks. The FDT application streams a large set of files across an open