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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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Quantum Computer Systems for Scientific Discovery
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Quantum Vulnerability Analysis to Guide Robust Quantum Computing System Design
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TRL Computer System User’s Guide
We have developed a wiki-based graphical user-interface system that implements our technology readiness level (TRL) uncertainty models. This document contains the instructions for using this wiki-based system.
The Formulary Model for Access Control and Privacy in Computer Systems
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Investigation of Optimizations for FPGA-based Controls Hardware for Experiments using Superconducting Quantum Computing Systems
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The Nature of Computer System Telemetry Data
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There’s more to a probabilistic neuromorphic computing system than noisy devices
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DGaaS: GPU as a Service on Distributed Computing System
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Parallel Computing Systems Software for Science, AI and Beyond
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Improving energy efficiency of Embedded DRAM Caches for High-end Computing Systems
With increasing system core-count, the size of last level cache (LLC) has increased and since SRAM consumes high leakage power, power consumption of LLCs is becoming a significant fraction of processor power consumption. To address this, researchers have used embedded DRAM (eDRAM) LLCs which consume low-leakage power. However, eDRAM caches consume a significant amount of energy in the form of refresh energy. In this paper, we propose ESTEEM, an energy saving technique for embedded DRAM caches. ESTEEM uses dynamic cache reconfiguration to turn-off a portion of the cache to save both leakage and refresh energy. It logically divides the cache sets into multiple modules and turns-off possibly different number of ways in each module. Microarchitectural simulations confirm that ESTEEM is effective in improving performance and energy efficiency and provides better results compared to a recently-proposed eDRAM cache energy saving technique, namely Refrint. For single and dual-core simulations, the average saving in memory subsystem (LLC+main memory) on using ESTEEM is 25.8% and 32.6%, respectively and average weighted speedup are 1.09X and 1.22X, respectively. Additional experiments confirm that ESTEEM works well for a wide-range of system parameters.
Processing NOAA Observation Data Over Hybrid Computer Systems for Comparative Climate Change Analysis
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Energy-Aware Resource Management for Computing Systems
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Utility Maximizing Dynamic Resource Management in an Oversubscribed Energy-Constrained Heterogeneous Computing System
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Feedback Computing in Leadership Compute Systems
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The Role of Container Technology in Reproducible Computer Systems Research.
Abstract not provided.
Scalable Energy Efficiency with Resilience for High Performance Computing Systems: A Quantitative Methodology
Energy efficiency and resilience are two crucial challenges for HPC systems to reach exascale. While energy efficiency and resilience issues have been extensively studied individually, little has been done to understand the interplay between energy efficiency and resilience for HPC systems. Decreasing the supply voltage associated with a given operating frequency for processors and other CMOS-based components can significantly reduce power consumption. However, this often raises system failure rates and consequently increases application execution time. In this work, we present an energy saving undervolting approach that leverages the mainstream resilience techniques to tolerate the increased failures caused by undervolting.