2017大型并行处理研讨会 Workshop on Large-Scale Parallel Processing: Practice and Experience

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活动简介

The Large-Scale Parallel Processing: Practice and Experience workshop is a forum that focuses on best-practice approaches to the design and utilization of computer systems that scale to thousands of processing elements and beyond. Large-scale systems, referred to by some as Extreme-scale or 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, but are not limited to, handling the substantial increase in per-chip core count, heterogeneity and specialized processor and intra-node architectures, complex communication and memory hierarchies, and communication and synchronization mechanisms. The workshop aims to bring together researchers and practitioners that have experience designing, building, and using such systems for a dynamic exchange of ideas. The goal is to span topics that range from hardware through the software and application stacks.

征稿信息

重要日期

2017-01-23

初稿截稿日期

2017-02-17

初稿录用日期

2017-02-27

终稿截稿日期

征稿范围

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.