Upcoming Machines - The Path to Exascale
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Computer Hardware↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Quantifying Scheduling Challenges for Exascale System Software
The move towards high-performance computing (HPC) ap- plications comprised of coupled codes and the need to dra- matically reduce data movement is leading to a reexami- nation of time-sharing vs. space-sharing in HPC systems. In this paper, we discuss and begin to quantify the perfor- mance impact of a move away from strict space-sharing of nodes for HPC applications. Specifically, we examine the po- tential performance cost of time-sharing nodes between ap- plication components, we determine whether a simple coor- dinated scheduling mechanism can address these problems, and we research how suitable simple constraint-based opti- mization techniques are for solving scheduling challenges in this regime. Our results demonstrate that current general- purpose HPC system software scheduling and resource al- location systems are subject to significant performance de- ciencies which we quantify for six representative applica- tions. Based on these results, we discuss areas in which ad- ditional research is needed to meet the scheduling challenges of next-generation HPC systems.
C.1.2 [Multiprocessors]: Parallel Processors↗
Programming Models for Parallel Architectures and Requirements for Pre-Exascale.
Abstract not provided.
Hammond, Simon David↗
XPRESS: eXascale Programming Environment and System Software.
Abstract not provided.
Brightwell, Ronald B.↗
A Flexible Conservative Remapping Framework for Exascale Computing
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Conservative Remapping↗
Building a Simulation Community for Solving Exascale Problems.
Abstract not provided.
Wilke, Jeremiah J↗
Balancing Productivity Portability and Performance - The Challenge for Programming Models at Exascale?.
Abstract not provided.
Hammond, Simon David↗
XASM: A Cross-Enclave Composition Mechanism for Exascale System Software.
Abstract not provided.
Evans, Noah↗
Scientific & Intelligence Exascale Visualization Analysis System
SIEVAS provides an immersive visualization framework for connecting multiple systems in real time for data science. SIEVAS provides the ability to connect multiple COTS and GOTS products in a seamless fashion for data fusion, data analysis, and viewing. It provides this capability by using a combination of micro services, real time messaging, and web service compliant back-end system.
Money, James H.↗