Signal and Power Integrity Design Methodology for High-Performance Flight Computing Systems

2021 ◽  
Author(s):  
Nicholas G. Franconi ◽  
Alan D. George ◽  
Alessandro D. Geist ◽  
Dennis Albaijes
Keyword(s):  
High Performance ◽  
Design Methodology ◽  
Power Integrity ◽  
Computing Systems

scholarly journals SELF-TIMED CIRCUITS AS A BASIS FOR DEVELOPING NEXT GENERATION HIGH-RELIABLE HIGH-PERFORMANCE COMPUTERS

2020 ◽  
Author(s):  
Aleksandr Zatsarinny ◽  
Yuriy Stepchenkov ◽  
Yuriy Diachenko ◽  
Yuriy Rogdestvenski
Keyword(s):  
Radiation Exposure ◽  
Circuit Design ◽  
High Performance ◽  
Design Methodology ◽  
Soft Errors ◽  
Next Generation ◽  
Computing Systems ◽  
Timed Circuits ◽  
High Performance Computers

The paper proposes design and circuitry solutions for the implementation of high-performance next generation computers. They are based on self-timed circuit design methodology and provide an increase in the tolerance of computing systems to soft errors resulting from induced noises and radiation exposure.

GPU-accelerated molecular dynamics: State-of-art software performance and porting from Nvidia CUDA to AMD HIP

2021 ◽  
pp. 109434202110082
Author(s):  
Nikolay Kondratyuk ◽  
Vsevolod Nikolskiy ◽  
Daniil Pavlov ◽  
Vladimir Stegailov
Keyword(s):  
Molecular Dynamics ◽  
High Performance ◽  
Software Performance ◽  
Computing Systems ◽  
Accelerated Molecular Dynamics ◽  
Nvidia Cuda ◽  
Software And Hardware ◽  
Management Capabilities ◽  
Utilization Time ◽  
Performance Computing

Classical molecular dynamics (MD) calculations represent a significant part of the utilization time of high-performance computing systems. As usual, the efficiency of such calculations is based on an interplay of software and hardware that are nowadays moving to hybrid GPU-based technologies. Several well-developed open-source MD codes focused on GPUs differ both in their data management capabilities and in performance. In this work, we analyze the performance of LAMMPS, GROMACS and OpenMM MD packages with different GPU backends on Nvidia Volta and AMD Vega20 GPUs. We consider the efficiency of solving two identical MD models (generic for material science and biomolecular studies) using different software and hardware combinations. We describe our experience in porting the CUDA backend of LAMMPS to ROCm HIP that shows considerable benefits for AMD GPUs comparatively to the OpenCL backend.

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