Performance Tuning of Scientific Applications (Chapman & by David H. Bailey, Robert F. Lucas, Samuel Williams

By David H. Bailey, Robert F. Lucas, Samuel Williams

With contributions from the most remarkable specialists within the box, functionality Tuning of medical functions offers present examine in functionality research. The ebook makes a speciality of the next parts. functionality tracking: Describes the cutting-edge in and software program instruments which are common for tracking and measuring functionality and dealing with huge amounts of information functionality research: Discusses sleek ways to computing device functionality benchmarking and provides effects that supply necessary perception into those stories functionality modeling: Explains how researchers deduce actual functionality versions from uncooked functionality facts or from different high-level features of a systematic computation computerized functionality tuning: Explores ongoing learn into computerized and semi-automatic options for optimizing machine courses to accomplish improved functionality on any computing device platform program tuning: presents examples that convey how the perfect research of functionality and a few deft alterations have ended in super excessive functionality functionality research has grown right into a full-fledged, refined box of empirical technology. Describing worthy examine in sleek functionality technological know-how and engineering, this booklet is helping real-world clients of parallel computers to higher comprehend either the functionality vagaries coming up in clinical functions and the sensible skill for making improvements to functionality. examine the ebook on HPCwire and insideHPC

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These counters can be used to determine the number of unread cache lines that hardware prefetchers have requested. A nonzero value for a hardware event associated with a hardware prefetcher will indicate that the prefetcher is enabled. 4 TLB Usage Optimization Chip multi-processor (CMP) systems may have shared DTLBs or a DTLB dedicated to each core. In either case, the ideal behavior is for the number of DTLB misses per core to decrease proportionally with problem size in the case of strong scaling, and to remain constant with weak scaling.

Counter Usage Modes . . . . . . . . . . . . . . . . . . . . . . 1 Counting Mode . . . . . . . . . . . . . . . . . . . . . 2 Sampling Mode . . . . . . . . . . . . . . . . . . . . . 3 Data Address Sampling . . . . . . . . . . . . . . . . . Uses of Hardware Counters . . . . . . . . . . . . . . . . . . . 1 Optimizing Cache Usage . . . . . . . . . . . . . . . . 2 Optimizing Bus Bandwidth .

Operating System Interfaces . . . . . . . . . . . . . . . . . . . 1 Perf Events . . . . . . . . . . . . . . . . . . . . . . . 2 Perfmon2 . . . . . . . . . . . . . . . . . . . . . . . . 3 Oprofile . . . . . . . . . . . . . . . . . . . . . . . . . PAPI in Detail . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Extension to Off-Processor Counters . . .

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