Simultac Fonton: A Fine-Grain Architecture for Extreme Performance beyond Moore's Law

Authors

  • Maciej Brodowicz Indiana University, Indiana, Bloomington
  • Thomas Sterling Indiana University, Indiana, Bloomington

DOI:

https://doi.org/10.14529/jsfi170203

Abstract

With nano-scale technology and Moore's Law end, architecture advance serves as the principal means of achieving enhanced efficiency and scalability into the exascale era. Ironically, the field that has demonstrated the greatest leaps of technology in the history of humankind, has retained its roots in its earliest strategy, the von Neumann architecture model which has imposed tradeoffs no longer valid for today's semiconductor technologies, although they were suitable through the 1980s. Essentially all commercial computers, including HPC, have been and are von Neumann derivatives. The bottlenecks imposed by this heritage are the emphasis on ALU/FPU utilization, single instruction issue and sequential consistency, and the separation of memory and processing logic ("von Neumann bottleneck"). Here the authors explore the possibility and implications of one class of non von Neumann architecture based on cellular structures, asynchronous multi-tasking, distributed shared memory, and message-driven computation. "Continuum Computer Architecture" is introduced as a genus of ultra-fine-grained architectures where complexity of operation is an emergent behavior of simplicity of design combined with highly replicated elements. An exemplar species of CCA, "Simultac" is considered comprising billions of simple elements, "fontons", of merged properties of data storage and movement combined with logical transformations. Employing the ParalleX execution model and a variation of the HPX+ runtime system software, the Simultac may provide the path to cost effective data analytics and machine learning as well as dynamic adaptive simulations in the trans-exaOPS performance regime.

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Published

2017-07-23

How to Cite

Brodowicz, M., & Sterling, T. (2017). Simultac Fonton: A Fine-Grain Architecture for Extreme Performance beyond Moore’s Law. Supercomputing Frontiers and Innovations, 4(2), 27–37. https://doi.org/10.14529/jsfi170203