Measuring High Performance Computing Productivity
International Journal of High Performance Computing Applications
A distributed dynamic aspect machine for scientific software development
Proceedings of the 1st workshop on Virtual machines and intermediate languages for emerging modularization mechanisms
pMatlab Parallel Matlab Library
International Journal of High Performance Computing Applications
Effective runtime scalability metric to measure productivity in high performance computing systems
Proceedings of the 5th conference on Computing frontiers
Groovy AOP: a dynamic AOP system for a JVM-based language
Proceedings of the 2008 AOSD workshop on Software engineering properties of languages and aspect technologies
A reinforcement learning framework for utility-based scheduling in resource-constrained systems
Future Generation Computer Systems
A reinforcement learning framework for utility-based scheduling in resource-constrained systems
A reinforcement learning framework for utility-based scheduling in resource-constrained systems
Productive petascale computing: requirements, hardware, and software
Productive petascale computing: requirements, hardware, and software
Enhancing productivity in high performance computing through systematic conditioning
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
An idiom-finding tool for increasing productivity of accelerators
Proceedings of the international conference on Supercomputing
An effective speedup metric for measuring productivity in large-scale parallel computer systems
The Journal of Supercomputing
Moving from petaflops to petadata
Communications of the ACM
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The Defense Advanced Research Projects Agency (DARPA) High Productivity Computing Systems (HPCS) program is focused on providing a new generation of economically viable high productivity computing systems for national security and for the industrial user community. The value of a high performance computing (HPC) system to a user includes many factors, such as execution time on a particular problem, software development time, direct hardware costs, and indirect administrative and maintenance costs. This special issue, which focuses on HPC productivity, brings together, for the first time, a series of novel papers written by several distinguished authors who share their views on this topic. The topic of productivity in HPC is very new and the authors have been encouraged to speculate. The goal of this first paper is to present an overarching context and framework for the other papers and to define some common ideas that have emerged in considering the problem of HPC productivity. In addition, this paper defines several characteristic HPC workflows that are useful for understanding how users exploit HPC systems, and discusses the role of activity and purpose benchmarks in establishing an empirical basis for HPC productivity.