Stochastic hardware architectures: A survey

Many emerging computer applications may be classified into recognition, mining, and synthesis (RMS) applications, or into stream-based media applications. One interesting and useful property of such applications is that they are tolerant to errors. In fact, these applications allow discrepancies in intermediate computations, but nevertheless are able to provide “acceptable” results. Research in this area leveraged this error tolerance in order to relax the zero-error tolerance requirement at the hardware level, and to shift error correction or concealment to the software application level. The main advantage of using such stochastic hardware architectures is in the major energy savings that are obtained since the circuits can be operated at reduced power supply levels. The hardware errors may be due to different components in the computer system. The purpose of this paper is to conduct a survey on techniques used in the design of stochastic architectures.

[1]  Lingamneni Avinash,et al.  Sustaining moore's law in embedded computing through probabilistic and approximate design: retrospects and prospects , 2009, CASES '09.

[2]  Christoph M. Kirsch,et al.  Incorrect systems: It's not the problem, It's the solution , 2012, DAC Design Automation Conference 2012.

[3]  Luis Ceze,et al.  Architecture support for disciplined approximate programming , 2012, ASPLOS XVII.

[4]  Douglas L. Jones,et al.  Stochastic computation , 2010, Design Automation Conference.

[5]  Rakesh Kumar,et al.  On the Theory of Stochastic Processors , 2010, 2010 Seventh International Conference on the Quantitative Evaluation of Systems.

[6]  Diana Franklin,et al.  Efficient fault tolerance in multi-media applications through selective instruction replication , 2008, WREFT '08.

[7]  John Sartori,et al.  Stochastic computing: Embracing errors in architecture and design of processors and applications , 2011, 2011 Proceedings of the 14th International Conference on Compilers, Architectures and Synthesis for Embedded Systems (CASES).

[8]  Quinn Jacobson,et al.  ERSA: error resilient system architecture for probabilistic applications , 2010, DATE 2010.

[9]  Frederic T. Chong,et al.  Characterization of Error-Tolerant Applications when Protecting Control Data , 2006, 2006 IEEE International Symposium on Workload Characterization.

[10]  John Sartori,et al.  Recovery-driven design: A power minimization methodology for error-tolerant processor modules , 2010, Design Automation Conference.

[11]  John Wawrzynek,et al.  Selectively Fortifying Reconfigurable Computing Device to Achieve Higher Error Resilience , 2012, J. Electr. Comput. Eng..

[12]  裕幸 飯田,et al.  International Technology Roadmap for Semiconductors 2003の要求清浄度について - シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について - , 2004 .

[13]  Donald Yeung,et al.  Application-Level Correctness and its Impact on Fault Tolerance , 2007, 2007 IEEE 13th International Symposium on High Performance Computer Architecture.

[14]  Subhasish Mitra,et al.  ERSA: Error Resilient System Architecture for probabilistic applications , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).

[15]  Swarup Bhunia,et al.  Low-Power Variation-Tolerant Design in Nanometer Silicon , 2011 .

[16]  John Sartori,et al.  Designing a processor from the ground up to allow voltage/reliability tradeoffs , 2010, HPCA - 16 2010 The Sixteenth International Symposium on High-Performance Computer Architecture.

[17]  Naresh R. Shanbhag,et al.  Minimum-Energy Operation Via Error Resiliency , 2010, IEEE Embedded Systems Letters.

[18]  Karthikeyan Sankaralingam,et al.  Relax: an architectural framework for software recovery of hardware faults , 2010, ISCA.

[19]  Rakesh Kumar,et al.  A numerical optimization-based methodology for application robustification: Transforming applications for error tolerance , 2010, 2010 IEEE/IFIP International Conference on Dependable Systems & Networks (DSN).

[20]  Kaushik Roy,et al.  SALSA: Systematic logic synthesis of approximate circuits , 2012, DAC Design Automation Conference 2012.

[21]  Lingamneni Avinash,et al.  What to do about the end of Moore's law, probably! , 2012, DAC Design Automation Conference 2012.

[22]  Venkatesh Akella,et al.  Reliability Requirements of Control , Address , and Data Operations in Error-Tolerant Applications , 2005 .

[23]  Kaushik Roy,et al.  Scalable effort hardware design: Exploiting algorithmic resilience for energy efficiency , 2010, Design Automation Conference.

[24]  Richard M. Karp,et al.  Algorithmic methodologies for ultra-efficient inexact architectures for sustaining technology scaling , 2012, CF '12.

[25]  Douglas L. Jones,et al.  Scalable stochastic processors , 2010, 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010).