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: There are several ways to approximate at software level. [[Memoization]] or fuzzy memoization (the use of a [[vector database]] for approximate retrieval from a cache, ''i.e.'' fuzzy caching) can be applied. Some [[iteration]]s of [[Loop (computing)|loops]] can be skipped (termed as [[loop perforation]]) to achieve a result faster. Some tasks can also be skipped, for example when a run-time condition suggests that those tasks are not going to be useful ([[task skipping]]). [[Monte Carlo algorithm]]s and [[Randomized algorithm]]s trade correctness for execution time guarantees.<ref>C.Alippi, Intelligence for Embedded Systems: a Methodological approach, Springer, 2014, pp. 283</ref> The computation can be reformulated according to paradigms that allow easily the acceleration on specialized hardware, e.g. a neural processing unit.<ref>{{Cite conference|last1=Esmaeilzadeh|first1=Hadi|last2=Sampson|first2=Adrian|last3=Ceze|first3=Luis|last4=Burger|first4=Doug|title=Neural acceleration for general-purpose approximate programs|conference=45th Annual IEEE/ACM International Symposium on Microarchitecture|year=2012|doi=10.1109/MICRO.2012.48|publisher=IEEE|pages=449–460|___location=Vancouver, BC}}</ref>
; Approximate system
: In an approximate system,<ref>{{Cite book|last1=Raha|first1=Arnab|last2=Raghunathan|first2=Vijay|title=Proceedings of the 54th Annual Design Automation Conference 2017 |chapter=Towards Full-System Energy-Accuracy Tradeoffs |date=2017|series=DAC '17|___location=New York, NY, USA|publisher=ACM|pages=74:1–74:6|doi=10.1145/3061639.3062333|isbn=9781450349277|s2cid=2503638}}</ref>
==Application areas==
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