BandiTS: Dynamic timing speculation using multi-armed bandit based optimization

2017 ◽  
Author(s):  
Jeff Jun Zhang ◽  
Siddharth Garg
Keyword(s):  
Timing Speculation

scholarly journals Managing contamination delay to improve Timing Speculation architectures

2016 ◽  
Vol 2 ◽  
pp. e79 ◽  
Author(s):  
Naga Durga Prasad Avirneni ◽  
Prem Kumar Ramesh ◽  
Arun K. Somani
Keyword(s):  
Performance Improvement ◽  
Short Path ◽  
Performance Enhancement ◽  
Propagation Delay ◽  
Performance Impact ◽  
Worst Case ◽  
Circuit Delay ◽  
Timing Speculation ◽  
Better Than

Timing Speculation (TS) is a widely known method for realizing better-than-worst-case systems. Aggressive clocking, realizable by TS, enable systems to operate beyond specified safe frequency limits to effectively exploit the data dependent circuit delay. However, the range of aggressive clocking for performance enhancement under TS is restricted by short paths. In this paper, we show that increasing the lengths of short paths of the circuit increases the effectiveness of TS, leading to performance improvement. Also, we propose an algorithm to efficiently add delay buffers to selected short paths while keeping down the area penalty. We present our algorithm results for ISCAS-85 suite and show that it is possible to increase the circuit contamination delay by up to 30% without affecting the propagation delay. We also explore the possibility of increasing short path delays further by relaxing the constraint on propagation delay and analyze the performance impact.

scholarly journals Implementing Adaptive Voltage Over-Scaling: Algorithmic Noise Tolerance vs. Approximate Error Detection

2019 ◽  
Vol 9 (2) ◽  
pp. 17 ◽  
Author(s):  
Roberto Giorgio Rizzo ◽  
Andrea Calimera
Keyword(s):  
Error Detection ◽  
Real Life ◽  
Cmos Technology ◽  
Approximate Computing ◽  
Noise Tolerance ◽  
Detection Mechanism ◽  
Quality Of Results ◽  
Timing Speculation ◽  
Open Issue

Adaptive Voltage Over-Scaling can be applied at run-time to reach the best tradeoff between quality of results and energy consumption. This strategy encompasses the concept of timing speculation through some level of approximation. How and on which part of the circuit to implement such approximation is an open issue. This work introduces a quantitative comparison between two complementary strategies: Algorithmic Noise Tolerance and Approximate Error Detection. The first implements a timing speculation by means approximate computing, while the latter exploits a more sophisticated approach that is based on the approximation of the error detection mechanism. The aim of this study was to provide both a qualitative and quantitative analysis on two real-life digital circuits mapped onto a state-of-the-art 28-nm CMOS technology.

scholarly journals Synergistic timing speculation for multi-threaded programs

2016 ◽  
Author(s):  
Atif Yasin ◽  
Jeff Jun Zhang ◽  
Hu Chen ◽  
Siddharth Garg ◽  
Sanghamitra Roy ◽  
...  
Keyword(s):  
Timing Speculation

Blueshift: Designing processors for timing speculation from the ground up.

2009 ◽  
Author(s):  
Brian Greskamp ◽  
Lu Wan ◽  
Ulya R. Karpuzcu ◽  
Jeffrey J. Cook ◽  
Josep Torrellas ◽  
...  
Keyword(s):  
Timing Speculation

TYMER: A Yield-based Performance Model for Timing-speculation SRAM

2020 ◽  
Author(s):  
Shan Shen ◽  
Liang Pang ◽  
Tianxiang Shao ◽  
Ming Ling ◽  
Xiao Shi ◽  
...  
Keyword(s):  
Performance Model ◽  
Timing Speculation
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