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SC20 Virtual Platform
Biography
Torsten Hoefler directs the Scalable Parallel Computing Laboratory (SPCL) at D-INFK ETH Zurich. He started his first professor appointment in 2011 at the University of Illinois at Urbana-Champaign, and has held visiting positions at Argonne National Laboratories, Sandia National Laboratories, and Microsoft Research Redmond (Station Q). He has published more than 200 papers in peer-reviewed international conferences and journals, has been awarded numerous best paper awards, and co-authored the latest versions of the MPI specification. Dr. Hoefler's research aims at understanding the performance of parallel computing systems ranging from parallel computer architecture through parallel programming to parallel algorithms. He is active in Weather and Climate applications, as well as Machine Learning, with a focus on Distributed Deep Learning. In those areas, he has coordinated tens of funded projects and an ERC Starting Grant on Data-Centric Parallel Programming. Additional information about Prof. Hoefler can be found on his homepage at htor.inf.ethz.ch.
Presentations
Paper
Graph Algorithms
Performance/Productivity Measurement and Evaluation
TP
Paper
Algorithms
Networks
Reconfigurable Computing
Routing
TP
Paper
Accelerators, FPGA, and GPUs
Applications
Architectures
TP
Posters
Virtual Student Cluster Competition
Student Program
TP
XO
Workshop
Accelerators, FPGA, and GPUs
Architectures
Emerging Technologies
Heterogeneous Systems
Reconfigurable Computing
W
Tutorial
Advanced
Extreme Scale Computing
MPI
Networks
Scalable Computing
TUT
Students@SC
Career Development
Community Engagement
Education, Training and Outreach
HPC Training and Education
Introductory
Student Program
TP
Tutorial
Advanced
Extreme Scale Computing
MPI
Networks
Scalable Computing
TUT
Tutorial
Accelerators, FPGA, and GPUs
Heterogeneous Systems
Parallel Programming Languages, Libraries, and Models
Software Engineering
TUT
Chair of Sessions
Workshop
Accelerators, FPGA, and GPUs
Architectures
Emerging Technologies
Heterogeneous Systems
Reconfigurable Computing
W
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