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LSPP 2016 - Workshop on Large-Scale Parallel Processing

Date2016-05-23 - 2016-05-26

Deadline2015-12-18

VenueChicago, USA - United States USA - United States

Keywords

Websitehttps://hpc.pnl.gov/conf/LSPP

Topics/Call fo Papers

The workshop on Large-Scale Parallel Processing is a forum that focuses on computer systems that utilize thousands of processors and beyond. Large-scale systems, referred to by some as extreme-scale and Ultra-scale, have many important research aspects that need detailed examination in order for their effective design, deployment, and utilization to take place. These include handling the substantial increase in multi-core on a chip, the ensuing interconnection hierarchy, communication, and synchronization mechanisms. Increasingly this is becoming an issue of co-design involving performance, power and reliability aspects. The workshop aims to bring together researchers from different communities working on challenging problems in this area for a dynamic exchange of ideas. Work at early stages of development as well as work that has been demonstrated in practice is equally welcome.
Of particular interest are papers that identify and analyze novel ideas rather than providing incremental advances in the following areas:
Large-scale systems: exploiting parallelism at large-scale, the coordination of large numbers of processing elements, synchronization and communication at large-scale, programming models and productivity
Novel architectures and experimental systems : the design of novel systems, the use emerging technologies such as Non-Volatile Memory, Silicon Photonics, application-specific accelerators and future trends.
Monitoring, Analysis, and Modeling: tools and techniques for gathering performance, power, thermal, reliability, and other data from existing large scale systems, analyzing such data offline or in real time for system tuning, and modeling of similar factors in projected system installations.
Multi-core: utilization of increased parallelism on a single chip, the possible integration of these into large-scale systems, and dealing with the resulting hierarchical connectivity.
Energy Management: Techniques, strategies, and experiences relating to the energy management and optimization of large-scale systems.
Applications: novel algorithmic and application methods, experiences in the design and use of applications that scale to large-scales, overcoming of limitations, performance analysis and insights gained.
Warehouse Computing: dealing with the issues in advanced datacenters that are increasingly moving from co-locating many servers to having a large number of servers working cohesively, impact of both software and hardware designs and optimizations to achieve best cost-performance efficiency.

Last modified: 2015-10-17 22:42:03