会议信息

HPC 2019: High Performance Computing Symposium

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嵌入截止倒计时徽章
HPC
截稿日期:
2019-01-08 Extended
通知日期:
2019-02-08
会议日期:
2019-04-29
会议地点:
Tucson, Arizona, USA
届数:
27
浏览: 17656   关注: 7   参加: 3

征稿

HPC 2019 (High Performance Computing Symposium) is an academic conference held in Tucson, Arizona, USA on 2019-04-29. The paper submission deadline is 2019-01-08 (extended). Acceptance notifications are sent on 2019-02-08.

The 2019 Spring Simulation Multi-Conference will feature the 27th High Performance Computing Symposium (HPC 2019), devoted to the impact of high performance computing and communications on simulations. Advances in novel and heterogeneous architectures, high-end computers, large data stores are ushering in a new era of high performance parallel and distributed simulations. Along with these new capabilities come new challenges in computing and system modeling. The goal of HPC 2019 is to encourage innovation in high performance computing and communication technologies and to promote synergistic advances in modeling methodologies and simulation. It will promote the exchange of ideas and information between universities, industry, supercomputing centers, and national laboratories about new developments in system modeling, high performance computing and communication, scientific computing as well as simulation. Topics of interest include but are not limited to: High performance computing issues in Big Data analytics High performance/large scale application case studies GPU for general purpose computations (GPGPU) Accelerator and co-processor computing Multicore and many-core computing Exascale challenges Power aware computing Cloud, distributed, and grid computing Asynchronous numerical methods and programming Hybrid system modeling and simulation Hybrid parallel or distributed algorithms Large scale visualization and data management Tools and environments for coupling parallel codes Parallel algorithms and architectures High performance software tools and techniques Resilience at the simulation level Reproducibility of application performance results
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