Salishan Conference on High Speed Computing
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Salishan 2017 Program

Full Program |  At-A-Glance Program

Keynote Address

Bits, Qubits, Neurons: The Near (and Not so Near) Future of Computing  |  William Camp, Camp Research

Session 1: Many-Core Computing - Application Challenges and Trinity/Cori Specifics

Intel's Many-Core Journey: Past, Present, and Future |  Alan Gara, Intel
The Impact of Increasing Memory System Diversity on Applications |  Gwen Voskuilen, Sandia National Laboratories
Trinity Center of Excellence: "I Can't Promise to Solve All of Your Problems, but I Can Promise You Won't Face Them Alone"| Hai Ah Nam, Los Alamos National Laboratory
Many-Cores for the Masses - Moving the NERSC Workload to Knights Landing and Beyond| Jack Deslippe, Lawrence Berkeley National Laboratory

Session 2: Heterogeneous Computing - Application Challenges and Sierra/Summit Specifics

Portable Performance with OpenMP in a Heterogeneous Era | Tom Scogland, Lawrence Livermore National Laboratory
Heterogenous Computing Challenges and Directions| John Danskin, Nvidia
Principles of Porting Disorder Therapy for the HPC Clinician: An Introduction | Fernanda Foertter, Oak Ridge National Laboratory
A Case for Intelligent (Co-)Design| Sean Treichler, Nvidia

Working Dinner

Winemaking: The Art and Science of Rotting Grapes to Perfection | James Osborne, Oregon State University

Session 3: Neuro-Inspired Computing

The Brain's Circuits Suggest Computing with High-Dimensional Vectors | Pentti Kanerva, University of California, Berkeley
TrueNorth Ecosystem | Dharmendra Modha, IBM
​Exploring Neuromorphic Computing a Lawrence Livermore National Laboratory | Brian Van Essen, Lawrence Livermore National Laboratory
Neural-Inspired Computing Algorithms and Hardware for Image Analysis and Cybersecurity Applications | Conrad James, Sandia National Laboratories

Random Access

A Case for Thread Mobility | Peter Kogge, University of Notre Dame
Taxonomy of HPC and DL - A Cry for Help | Dale Southard, Nvidia
The Goldilocks Principle is Wrong | Marc Snir, University of Illinois
Any Sufficiently Advanced Compiler.... | Michael Wolfe, Nvidia
Solving the Information Technology Energy Challenges Beyond Moore's Law: A New Path to Scaling | Bill Harrod, DOE
Exascale by 2021-23 - Truth of Myth? | Shekhar Borkar, Qualcomm
Some Interesting Observations on the Knight's Landing | John Levesque, Cray
China HPC Update and Exascale Predictions | David Kahaner, Asian Technology Information Program 

Student Posters

Monte Carlo Transport on Modern Architectures: Quicksilver at the LLNL COE| Ryan Bleile, University of Oregon, Eugene
Gradient Quantization for Data-Parallel DNN Training | Nikoli Dryden, University of Illinois Urbana-Champaign
Kokkos Autotuning for SpMV Kernels on High-Performance Accelerators | Simon Garcia De Gonzalo, University of Illinois Urbana-Champaign
Finding Maximum Cliques on a Quantum Annealer | Georg Hahn, Imperial College London
A RAJA-based Tuning Framework for Multi-Platform Performance Prediction | William Killian, University of Delaware
Sparse Coding on Stereo Video for Object Detection | Sheng Lundquist, Portland State University
 | Ciaran Ryan-Anderson, University of New Mexico
Designing Neural Information Processing at Scale: Some Lessons from Self-Organization in Spiking Neural Networks | Felix Wang, University of Illinois Urbana-Champaign
 Effective OpenMP Implementations | Yuliana Zamora, University of New Mexico

Session 4: Quantum Computing

Quantum High Performance Computing | Matthias Troyer, Microsoft
Quantum Computing: Cladogenesis Beyond Exascale HPC | Andrew Landahl, Sandia National Laboratories
Quantum Annealing at NASA: Current Status | Rupak Biswas, NASA Ames Research Center
What to Do with More than 1000 Quantum Bits | Scott Pakin, Los Alamos National Laboratory

Session 5: Crosscutting Fragments

128 Bit, Exascale Memory Reference Models for Next Generation, Exabyte Capacity Physical Memory Systems | Steven Wallach, Micron
2017-monroe.pdfProbabilistic Computing in the Post-Moore's Era| Laura Monroe, Los Alamos National Laboratory
Towards Always-On Integrated Performance Analysis Tools| Matthew LeGendre,  Lawrence Livermore National Laboratory
Photos courtesy of John Daly
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