scholarly journals A Machine Learning-Genetic Algorithm (ML-GA) Approach for Rapid Optimization Using High-Performance Computing

2018 ◽  
Vol 11 (5) ◽  
pp. 291-306 ◽  
Author(s):  
Ahmed Abdul Moiz ◽  
Pinaki Pal ◽  
Daniel Probst ◽  
Yuanjiang Pei ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Genetic Algorithm ◽  
High Performance Computing ◽  
High Performance ◽  
Performance Computing

scholarly journals Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

2019 ◽  
Vol 16 (2) ◽  
pp. 541-564
Author(s):  
Mathias Longo ◽  
Ana Rodriguez ◽  
Cristian Mateos ◽  
Alejandro Zunino
Keyword(s):  
Machine Learning ◽  
High Performance Computing ◽  
Computer Simulations ◽  
High Performance ◽  
Machine Learning Algorithms ◽  
Energy Usage ◽  
Energy Aware ◽  
Scientific Application ◽  
Performance Computing ◽  
Reducing Energy

In-silico research has grown considerably. Today?s scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.

scholarly journals Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing

Joule ◽  
2018 ◽  
Vol 2 (8) ◽  
pp. 1410-1420 ◽  
Author(s):  
Juan-Pablo Correa-Baena ◽  
Kedar Hippalgaonkar ◽  
Jeroen van Duren ◽  
Shaffiq Jaffer ◽  
Vijay R. Chandrasekhar ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Performance Computing ◽  
High Performance ◽  
Materials Development ◽  
Performance Computing
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