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HPEC '19

October 15, 2019

Organized by Lincoln Laboratories, and with sponsorship, this year from DELL, Hewlett Packard, Intel Corp, NVIDIA, and MITRE, IEEE HPEC 2019, was held September 24th to 26th, 2019 in Waltham, MA.
This year's speakers included Marc Hamilton (Nvidia VP of Solutions Architecture and Engineering) "GPU Accelerated Machine Learning", Dr. Michael Rosenfield (IBM VP Data Centric Solutions) "Future Computing Systems", Stan Reiss (Matrix Partners) "Brilliant Technologists Building Cool Stuff", Prof. Julian Shun (MIT CSAIL) "Large-Scale Graph Processing", Mark Hamilton (Microsoft) "Microsoft MLSpark: Unifying Machine Learning Ecosystems at Massive Scales", Jaya Shankar (Mathworks) "Deploying High-Performance Deep Learning Applications", Prof. Yunsi Fei (Northeastern University) "Evaluating Fault Resilience of Compressed Deep Neural Networks",  Dr. Robert Freeman (Director, Research Technology Operations, Harvard Business School), and Julie Ma (Project Leader, Northeast Cyberteam Initiative, MGHPCC) "Northeast Cyberteam: A Workforce Development Strategy for Research Computing."
The meeting's technical program included tutorials from industry and academic experts, demonstrations, and poster sessions, among them: the Julia Programming LanguageRemote Sensing for Humanitarian Assistance & Disaster Relief (organized by Dr. John Aldridge, and Dan DumanisAndrew Weinert (MIT LL), HPSEC: High Performance Secure Extreme Computing (organized by Dr. Michael Vai (MIT LL), BRAIDS: Boosting Resilience through Artificial Intelligence and Decision Support (organized by Dr. Alexia Schultz (MIT LL), Dr. Pierre Trepagnier (MIT LL), Dr. Igor Linkov (Corps of Engineers), Matthew Bates (Corps of Engineers)), and Bridging Quantum and High Performance Computing (organized by Prof. Patrick Dreher (NC State Univ), and Scaling HPC Education (organized by Dr. Julie Mullen (MIT LLSC) and Lauren Milechen (MIT EAPS).)
Special events included the MIT/Amazon/IEEE Graph Challenge, a GraphBLAS forum to define standard building blocks for graph algorithms (organized by Dr Timothy Mattson (Intel), Dr Scott McMillan (CMU SEI), and Dr Marcin Zalewski (PNNL)), and the IEEE Innovation in Societal Infrastructure Award.
The 2020 IEEE High Performance Extreme Computing Conference, will take place from the 22nd to the 24th of September 2020 in Waltham, MA. The submission deadline for papers is May 18, 2019. Submission dates for GraphChallenge will be posted here graphchallenge.mit.edu. For more information visit ieee-hpec.org.

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Scaling High Performance Computing Education MGHPCC News

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HPEC'18 MGHPCC News
HPEC'17 MGHPCC News
 

Research projects

A Future of Unmanned Aerial Vehicles
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Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
SEQer - Sequence Evaluation in Realtime
Revolutionizing Materials Design with Computational Modeling
Remote Sensing of Earth Systems
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
NeuraChip
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Genome Forecasting
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Energy Transport and Ultrafast Spectroscopy Lab
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Cyber-Physical Communication Network Security
Asteroid Data Mining
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
ACAS X: A Family of Next-Generation Collision Avoidance Systems
Neurocognition at the Wu Tsai Institute, Yale
Computational Modeling of Biological Systems
Computational Molecular Ecology
Social Capital and Economic Mobility
Building for Floods
Better Pathogen Targeting
Tracking Environmental Health Risks
AI for Cancer Diagnosis
Microplastic-Free by Design
Supporting Data-intensive Social Science
Sailing the Symbiosis Seascape
Wrangle Range Modeling
Shining a Light on Dark Matter
Grid Responsive Data Centers
Multifunctional 3D-Printed Materials
AI Pareidolia
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Staving off the Banana Apocalypse
CRISPR Mice, Smarter Science
AI That Speaks Human About Health
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