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      {
         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/28b341984a107175be05eebdda39e6c12/clausbraun",         
         "tags" : [
            "AxC","CCG","PCG","SimTech","approximate","computing","conjugate","error-correction","error-detection","fault-tolerance","gradient","linear","myown","preconditioned","solver","sparse","systems"
         ],
         
         "intraHash" : "8b341984a107175be05eebdda39e6c12",
         "interHash" : "819e882fc0ec03e0c6e332411bfbf42d",
         "label" : "Applying Efficient Fault Tolerance to Enable the Preconditioned Conjugate Gradient Solver on Approximate Computing Hardware",
         "user" : "clausbraun",
         "description" : "",
         "date" : "2018-03-19 16:15:07",
         "changeDate" : "2018-03-19 15:34:51",
         "count" : 6,
         "pub-type": "inproceedings",
         "booktitle": "Proceedings of the IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT'16)",
         "year": "2016", 
         "url": "", 
         
         "author": [ 
            "Alexander Schöll","Claus Braun","Hans-Joachim Wunderlich"
         ],
         "authors": [
         	
            	{"first" : "Alexander",	"last" : "Schöll"},
            	{"first" : "Claus",	"last" : "Braun"},
            	{"first" : "Hans-Joachim",	"last" : "Wunderlich"}
         ],
         "pages": "21-26","abstract": "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.",
         "file" : "http://www.iti.uni-stuttgart.de/fileadmin/rami/files/publications/2016/DFT_SchoeBW2016.pdf",
         
         "doi" : "http://dx.doi.org/10.1109/DFT.2016.7684063",
         
         "bibtexKey": "SchoeBW2016"

      }
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         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/292cad6c6d7a90044e7289f504f6f4cf7/clausbraun",         
         "tags" : [
            "ABFT","GPGPU","SimTech","algorithm-based","computing","errors","fault","fault-tolerance","myown","scientific","simulation"
         ],
         
         "intraHash" : "92cad6c6d7a90044e7289f504f6f4cf7",
         "interHash" : "852ec5b9e00df1c4437700418d91759c",
         "label" : "Efficacy and Efficiency of Algorithm-Based Fault Tolerance on GPUs",
         "user" : "clausbraun",
         "description" : "",
         "date" : "2018-03-19 16:15:07",
         "changeDate" : "2018-03-19 15:29:40",
         "count" : 7,
         "pub-type": "inproceedings",
         "booktitle": "Proceedings of the IEEE International On-Line Testing Symposium (IOLTS'13)",
         "year": "2013", 
         "url": "", 
         
         "author": [ 
            "Hans-Joachim Wunderlich","Claus Braun","Sebastian Halder"
         ],
         "authors": [
         	
            	{"first" : "Hans-Joachim",	"last" : "Wunderlich"},
            	{"first" : "Claus",	"last" : "Braun"},
            	{"first" : "Sebastian",	"last" : "Halder"}
         ],
         "pages": "240--243","abstract": "Computer simulations drive innovations in science and industry, and they are gaining more and more importance. However, their high computational demand generates extraordinary challenges for computing systems. Typical highperformance computing systems, which provide sufficient performance and high reliability, are extremly expensive.\r\nModern GPUs offer high performance at very low costs, and they enable simulation applications on the desktop. However, they are increasingly prone to transient effects and other reliability threats. To fulfill the strict reliability requirements in scientific computing and simulation technology, appropriate fault tolerance measures have to be integrated into simulation applications for GPUs. Algorithm-Based Fault Tolerance on GPUs has the potential to meet these requirements.\r\nIn this work we investigate the efficiency and the efficacy of ABFT for matrix operations on GPUs. We compare ABFT against fault tolerance schemes that are based on redundant computations and we evaluate its error detection capabilities",
         "file" : "http://www.iti.uni-stuttgart.de/fileadmin/rami/files/publications/2013/IOLTS_WundeBH2013.pdf",
         
         "doi" : "http://dx.doi.org/10.1109/IOLTS.2013.6604090",
         
         "bibtexKey": "WundeBH2013"

      }
	  
   ]
}