PUMA publications for /user/clausbraun/sparse%20axchttps://puma.ub.uni-stuttgart.de/user/clausbraun/sparse%20axcPUMA RSS feed for /user/clausbraun/sparse%20axc2024-03-19T12:55:58+01:00Applying Efficient Fault Tolerance to Enable the Preconditioned Conjugate Gradient Solver on Approximate Computing Hardwarehttps://puma.ub.uni-stuttgart.de/bibtex/28b341984a107175be05eebdda39e6c12/clausbraunclausbraun2018-03-19T16:15:07+01:00AxC CCG PCG SimTech approximate computing conjugate error-correction error-detection fault-tolerance gradient linear myown preconditioned solver sparse systems <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Schöll" itemprop="url" href="/person/1819e882fc0ec03e0c6e332411bfbf42d/author/0"><span itemprop="name">A. Schöll</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Claus Braun" itemprop="url" href="/person/1819e882fc0ec03e0c6e332411bfbf42d/author/1"><span itemprop="name">C. Braun</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hans-Joachim Wunderlich" itemprop="url" href="/person/1819e882fc0ec03e0c6e332411bfbf42d/author/2"><span itemprop="name">H. Wunderlich</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT'16)</span>, </em></span><em>page <span itemprop="pagination">21-26</span>. </em>(<em><span>2016<meta content="2016" itemprop="datePublished"/></span></em>)</span>Mon Mar 19 16:15:07 CET 2018Proceedings of the IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT'16)21-26{Applying Efficient Fault Tolerance to Enable the Preconditioned Conjugate Gradient Solver on Approximate Computing Hardware}2016AxC CCG PCG SimTech approximate computing conjugate error-correction error-detection fault-tolerance gradient linear myown preconditioned solver sparse systems A new technique is presented that allows to execute the preconditioned conjugate gradient (PCG) solver on approximate hardware while ensuring correct solver results. This technique expands the scope of approximate computing to scientific and engineering applications. The changing error resilience of PCG during the solving process is exploited by different levels of approximation which trade off numerical accuracy and hardware utilization. Such approximation levels are determined at runtime by periodically estimating the error resilience. An efficient fault tolerance technique allows reductions in hardware utilization by ensuring the continued exploitation of maximum allowed energy-accuracy trade-offs. Experimental results show that the hardware utilization is reduced on average by 14.5% and by up to 41.0% compared to executing PCG on accurate hardware.