Exploiting Errors for Efficiency

Author:

Stanley-Marbell Phillip1ORCID,Alaghi Armin2,Carbin Michael3,Darulova Eva4,Dolecek Lara5,Gerstlauer Andreas6,Gillani Ghayoor7,Jevdjic Djordje8,Moreau Thierry2,Cacciotti Mattia9,Daglis Alexandros10,Jerger Natalie Enright11,Falsafi Babak12,Misailovic Sasa13,Sampson Adrian14,Zufferey Damien4

Affiliation:

1. University of Cambridge, Cambridge, UK

2. University of Washington

3. Massachusetts Institute of Technology, Cambridge, MA, USA

4. Max Planck Institute for Software Systems, Kaiserslautern, Germany

5. University of California at Los Angeles, Los Angeles, CA, USA

6. The University of Texas at Austin, Austin, TX, USA

7. University of Twente, The Netherlands

8. National University of Singapore, Singapore

9. École Polytechnique Fédérale de Lausanne

10. Georgia Institute of Technology, Atlanta, GA, USA

11. University of Toronto, Toronto ON, Canada

12. École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

13. University of Illinois at Urbana-Champaign, Urbana, IL

14. Cornell University, Ithaca NY

Abstract

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, system software, and programming language compilers or their runtime systems can trade deviations from correct behavior for lower resource usage. We present, for the first time, a synthesis of research results on computing systems that only make as many errors as their end-to-end applications can tolerate. The results span the disciplines of computer-aided design of circuits, digital system design, computer architecture, programming languages, operating systems, and information theory. Rather than over-provisioning the resources controlled by each of these layers of abstraction to avoid errors, it can be more efficient to exploit the masking of errors occurring at one layer and thereby prevent those errors from propagating to a higher layer. We demonstrate the potential benefits of end-to-end approaches using two illustrative examples. We introduce a formalization of terminology that allows us to present a coherent view across the techniques traditionally used by different research communities in their individual layer of focus. Using this formalization, we survey tradeoffs for individual layers of computing systems at the circuit, architecture, operating system, and programming language levels as well as fundamental information-theoretic limits to tradeoffs between resource usage and correctness.

Funder

Swiss National Science Foundation

Royal Society

EPFL EcoCloud Research Center

Alan Turing Institute

EPSRC

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference234 articles.

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