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Designing reliable systems, while eschewing the high overheads of conventional fault tolerance techniques, is a critical challenge in the deeply scaled CMOS and post-CMOS era. To address this challenge, we leverage the intrinsic resilience of application domains such as multimedia, recognition, mining, search, and analytics where acceptable outputs are produced despite occasional approximate computations. We propose stochastic checkers (checkers designed using stochastic logic) as a new approach to performing error checking in an approximate manner at greatly reduced overheads. Stochastic checkers are inherently inaccurate and require long latencies for computation. To limit the loss in error coverage, as well as false positives (correct outputs flagged as erroneous), caused due to the approximate nature of stochastic checkers, we propose input permuted partial replicas of stochastic logic, which improves their accuracy with minimal increase in overheads. To address the challenge of long error detection latency, we propose progressive checking policies that provide an early decision based on a prefix of the checker’s output bitstream. This technique is further enhanced by employing progressively accurate binary-to-stochastic converters. Across a suite of error-resilient applications, we observe that stochastic checkers lead to greatly reduced overheads (29.5% area and 21.5% power, on average) compared with traditional fault tolerance techniques while maintaining high coverage and very low false positives. [ABSTRACT FROM PUBLISHER]

The H.264 encoded video is highly sensitive to loss of motion vectors during transmission. Several statistical techniques are proposed for recovering such lost motion vectors. These use only the motion vectors that belong to the macroblocks that are horizontally or vertically adjacent to the lost macroblock, to recover the latter. Intuitively this is one of the main reasons behind why these techniques yield inferior solutions in scenarios where there is a non-linear motion. This paper proposes B-Spline based statistical techniques that comprehensively address the motion vector recovery problem in the presence of different types of motions that include slow, fast/sudden, continuous and non-linear movements. Testing the proposed algorithms with different benchmark video sequences shows an average improvement of up to 2 dB in the Peak Signal to Noise Ratio of some of the recovered videos, over existing techniques. A 2 dB improvement in PSNR is very significant from an application point of view. [ABSTRACT FROM AUTHOR]

With the emergence of complex high-performance microprocessors, functional test generation has become a crucial design step. Constraint-based test generation is a well-studied directed behavioral level functional test generation paradigm. The paradigm involves conversion of a given circuit model into a set of constraints and employing constraint solvers to generate tests for it. However, automatic extraction of constraints from a given behavioral hardware design language (HDL) model remained a challenging open problem. This paper proposes an approach for automatic extraction of word-level model constraints from the behavioral verilog HDL description. The scenarios to be tested are also expressed as constraints. The model and the scenario constraints are solved together using an integer solver to arrive at the necessary functional test. The effectiveness of the approach is demonstrated by automatically generating the constraint models for: 1) an exclusive-shared-invalid multiprocessor cache coherency model and 2) the 16-bit DLX-architecture, from their respective Verilog-based behavioral models. Experimental results that generate test vectors for high level scenarios like pipeline hazards, cache miss, etc., spanning over multiple time-frames are presented. [ABSTRACT FROM AUTHOR]

The article reports on research for generating tolerant and safe on-chip variations to avoid false delay test failures. A framework is proposed that minimizes peak power needs and pattern optimization flow. Global peak power is addressed and defined as the maximum total power exhausted by the entire chip during one clock cycle.