Jack Dongarra, University of Tennessee
Today Intel posted the Agenda for its all-new HPC Developer Conference. Beginning with a keynote from Jack Dongarra from the University of Tennessee, the event takes place Nov. 14-15, just prior to SC15 in Austin, Texas.
“The Intel HPC Developer Conference offers high levels of access. This is your best opportunity to connect with Intel architecture experts, meet HPC industry leaders, and build a lasting network of peers. This is your best opportunity to connect with Intel architecture experts, meet HPC industry leaders, and build a lasting network of peers. The conference will also offer insights into the future of HPC with Intel experts on visualization, machine learning, software tools and much more.”
Tech Sessions include:
- A Brief Introduction to OpenFabrics Interfaces (libfabric)
- Topic: Getting Smart With Intel’s Roadmap: Intel Xeon and Intel Xeon Phi
- Scientific Insights and Discoveries through Scalable High Performance Computing at LRZ
- SMB Cloud Considerations
- SDVis Overview, and OpenSWR & Fast SW Rendering within MESA
- Two Talks in One: OpenSWR Case Study: CEI Ensight; Case Study: Integrating OSPRay in VMD for Biomolecular Vis.
- High Performance Clustering for Trillion Particle Simulations
- Building A Real-Time, Closed Loop fMRI Data Analysis System for Neuroscience Experiments
- Pushing Machine Learning to a New Level with Intel Xeon and Intel Xeon Phi Processors
- hStreams – Easing the Way to Parallelism on Heterogeneous Platforms
- OpenMP and the Intel Compiler
- Optimizing for Data Locality: A Case Study that Spans Multiple Application Domains
- Introduction to Advanced Data Movement and Analysis Toolkit (ADAMANT), a tool to analyze HPC Application Data Structures
- Distributed Persistent Memory Programming – Software Mechanisms to Access Remote NVM
- Teaching Parallelism to Undergraduates
- Working Together on Frameworks for HPC systems
- Diving into Intel’s HPC Scalable System Framework Plans
- Job Launching – Keeping Pace with Expanding Complexities
- Developing for the New Memory Hierarchy
- Using OpenStack to Manage a Data Analytics HPC Cluster
- Effective Parallel Optimizations with Intel Fortran
- High Performance Python Offloading to the Intel® Xeon Phi™ Coprocessor
- Profiling at Scale
- Designing Parallel Financial Analytics Libraries using a Pattern Oriented Approach
- The SeqAn C++ library for efficient NGS sequence analysis – applications and HPC modernization using generic programming
- Calculating The Weather: A New Generation of HPC at the Met Office
- Implementing HPC in Oil and Gas, History, Technology and Business Value
- MCDRAM (High Bandwidth Memory) on Knights Landing – Analysis Methods/Tools
- Making Sense of Shared Memory Models: shmem, PGAS, Coarray Fortran, etc.
