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The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast - how size scaling drives performance Implicit parallelism - how a sequential program can be executed faster with parallelism Dynamic locality - skirting physical limits, by arranging data in a smaller space Parallelism - increasing performance with teams of workers.
When you click on links to various merchants on this site and make a purchase, this can result in this site earning a commission. Affiliate programs and affiliations include, but are not limited to, the eBay Partner Network.