Babak Falsafi – författare

This book provides readers with an overview of the architectures, programming frameworks, and hardware accelerators for typical cloud computing applications in data centers. The authors present the most recent and promising solutions, using hardware accelerators to provide high throughput, reduced latency and higher energy efficiency compared to current servers based on commodity processors. Readers will benefit from state-of-the-art information regarding application requirements in contemporary data centers, computational complexity of typical tasks in cloud computing, and a programming framework for the efficient utilization of the hardware accelerators.

Since the 1970’s, microprocessor-based digital platforms have been riding Moore’s law, allowing for doubling of density for the same area roughly every two years. However, whereas microprocessor fabrication has focused on increasing instruction execution rate, memory fabrication technologies have focused primarily on an increase in capacity with negligible increase in speed. This divergent trend in performance between the processors and memory has led to a phenomenon referred to as the “Memory Wall.” To overcome the memory wall, designers have resorted to a hierarchy of cache memory levels, which rely on the principal of memory access locality to reduce the observed memory access time and the performance gap between processors and memory. Unfortunately, important workload classes exhibit adverse memory access patterns that baffle the simple policies built into modern cache hierarchies to move instructions and data across cache levels. As such, processors often spend much time idling upon a demand fetch of memory blocks that miss in higher cache levels. Prefetching—predicting future memory accesses and issuing requests for the corresponding memory blocks in advance of explicit accesses—is an effective approach to hide memory access latency. There have been a myriad of proposed prefetching techniques, and nearly every modern processor includes some hardware prefetching mechanisms targeting simple and regular memory access patterns. This primer offers an overview of the various classes of hardware prefetchers for instructions and data proposed in the research literature, and presents examples of techniques incorporated into modern microprocessors.

This book provides readers with an overview of the architectures, programming frameworks, and hardware accelerators for typical cloud computing applications in data centers. The authors present the most recent and promising solutions, using hardware accelerators to provide high throughput, reduced latency and higher energy efficiency compared to current servers based on commodity processors. Readers will benefit from state-of-the-art information regarding application requirements in contemporary data centers, computational complexity of typical tasks in cloud computing, and a programming framework for the efficient utilization of the hardware accelerators.

WelcometotheproceedingsofthePower-AwareComputerSystems(PACS2002) workshopheld in conjunction with the 8th InternationalSymposium on High PerformanceComputerArchitecture(HPCA-8). Improvementsincomputers- temperformancehavebeenaccompaniedbyanalarmingincreaseinpowerand energydissipation,leading tohigher costandlowerreliabilityinallcomputer systemsmarketsegments. Thehigherpower/energydissipationhasalsosign- icantlyreducedbatterylife inportablesystems. Whilecircuit-leveltechniques continuetoreducepowerandenergy,alllevelsofcomputersystemsarebeing usedtoaddresspowerandenergyissues. PACS2002wasthesecondworkshopin itsseriestoaddresspower-/energy-awarenessatalllevelsofcomputersystems andbroughttogetherexpertsfromacademiaandindustry. Theseproceedingsincluderesearchpapersspanningawidespectrumof- eas in power-aware systems. We have grouped the papers into the following categories:(1)power-awarearchitectureandmicroarchitecture,(2)power-aware real-time systems, (3) power modeling and monitoring, and (4) power-aware operatingsystemsandcompilers. The?rstgroupofpapersproposepower-awaretechniquesfortheprocessor pipeline using adaptiveresizing of power-hungrymicroarchitecturalstructures andclockgating,andpower-awarecachedesignbyavoidingtagchecksin- riodswhenthetagshavenotchanged.Thisgroupalsoincludesideastoadapt energyandperformancedynamicallybydetectingregionsofapplicationatr- timewherethesupplyvoltagemaybescaledtoreducepowerwithabounded decrease in performance. Lastly, a paper on multiprocessor designs trades o? computingcapacityandfunctionalityforimprovedenergypercyclebysched- ing simple tasks on low-end and low-energy processorsand complex tasks on high-endprocessors. Thesecondgroupofpaperstargetreal-timesystemsincludingideasonal- complexityheuristicwhichschedulesreal-timetaskssuchthatnotaskmissesits deadlineandthetotalenergysavingsaremaximized. Theotherpapersinthis group(1)tunethesystem-levelparallelismtothecurrent-levelofpower/energy availabilityandoptimizethesystempowerutilization,and(2)performadaptive texturemappinginreal-time3Dgraphicssystemsbasedonamodelofhuman visualperceptiontoachievesigni?cantpowersavingswithoutnoticeableimage qualitydegradation. Thethirdgroupofpapersfocusonpowermodelingandmonitoringincluding statisticalpro?lingtodetectsoftwarehotspotsofpower,andusingPetriNetsto modelDRAMpowerpolicies. Thisgroupalsoincludesasimulatorforevaluating theperformanceandpowerofdynamicvoltagescalingalgorithms.Thelast groupconcentratesonOS and compilersfor lowpower. The ?rst paperproposesapplication-issueddirectivestosetthepowermodesindevices suchasadiskdrive. Thesecondpaperproposespoliciesforcluster-widepower VI Preface management. Thepoliciesemploycombinationsofdynamicvoltagescalingand turningonando?toreduceoverallclusterpower. PACS2002wasahighlysuccessfulforumduetothehigh-qualitysubmissions, theenormouse?ortsoftheprogramcommitteeandthekeynotespeaker,andthe attendees. WewouldliketothankRonnyRonenforanexcellentkeynotespeech, showingthetechnologicalscalingtrendsandtheirimpactonenergy/powerc- sumption in general-purposemicroprocessors,and pinpointing recentmicro- chitecturalstrategiestoachievemorepower-e?cientmicroprocessors. Wewould like to also thank Antonio Gonzalez, Andreas Moshovos,John Kalamatianos, andothermembersoftheHPCA-8organizingcommitteewhohelpedarrange forlocalaccomodationandpublicizetheworkshop. February2002 BabakFalsa?andT. N. Vijaykumar PACS2002 Program Committee BabakFalsa?,CarnegieMellonUniversity(co-chair) T. N.Vijaykumar,PurdueUniversity(co-chair) DaveAlbonesi,UniversityofRochester KrsteAsanovic,MassachusettsInstituteofTechnology IrisBahar,BrownUniversity LucaBenini,UniversityofBologna DougCarmean,Intel Yuen Chan,IBM KeithFarkas,CompaqWRL MaryJaneIrwin,PennsylvaniaStateUniversity StefanosKaxiras,AgereSystems PeterKogge,UniversityofNotreDame UliKremer,RutgersUniversity AlvinLebeck,DukeUniversity AndreasMoshovos,UniversityofToronto RajRajkumar,CarnegieMellonUniversity KaushikRoy,PurdueUniversity Table of Contents Power-Aware Architecture/Microarchitecture Early-StageDe?nitionofLPX:ALowPowerIssue-ExecuteProcessor ...1 P. Bose,D. Brooks,A. Buyuktosunoglu,P. Cook,K. Das,P. Emma, M. Gschwind,H. Jacobson,T. Karkhanis,P. Kudva,S. Schuster, J. Smith,V. Srinivasan,V. Zyuban,D. Albonesi,andS. Dwarkadas DynamicTag-CheckOmission: ALowPowerInstructionCacheArchitecture ExploitingExecutionFootprints ...18 KojiInoue,VasilyMoshnyaga,andKazuakiMurakami AHardwareArchitecture forDynamicPerformanceandEnergyAdaptation...33 PhillipStanley-Marbell,MichaelS. Hsiao,andUlrichKremer Multi-processorComputerSystemHavingLowPowerConsumption ...53 C. MichaelOlsenandL.AlexMorrow Power-Aware Real-TimeSystems AnIntegratedHeuristicApproach toPower-AwareReal-TimeScheduling...68 PedroMejia,EugeneLevner,andDanielMoss'e Power-AwareTaskMotionforEnhancingDynamicRange ofEmbeddedSystemswithRenewableEnergySources ...84 JinfengLiu,PaiH. Chou,andNaderBagherzadeh ALow-PowerContent-AdaptiveTextureMappingArchitecture forReal-Time3DGraphics ...99 JeongseonEuh,JeevanChittamuru,andWayneBurleson Power Modelingand Monitoring Energy-DrivenStatisticalSampling:DetectingSoftwareHotspots ...110 FayChang,KeithI. Farkas,andParthasarathyRanganathan ModelingofDRAMPowerControlPolicies UsingDeterministicandStochasticPetriNets ...130 XiaoboFan,CarlaS. Ellis,andAlvinR. Lebeck SimDVS:AnIntegratedSimulationEnvironment forPerformanceEvaluationofDynamicVoltageScalingAlgorithms ...

This book contributes the thoroughly refereed post-proceedings of the Third International Workshop on Power-Aware Computer Systems, PACS 2003, held in San Diego, CA, USA in December 2003.The 14 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 43 submissions. The papers span a wide spectrum of topics in power-aware systems; they are organized in topical sections on compilers, embedded systems, microarchitectures, and cache and memory systems.

Welcome to the proceedings of the Power-Aware Computer Systems (PACS 2004) workshop held in conjunction with the 37th Annual International Sym- sium on Microarchitecture (MICRO-37). The continued increase of power and energy dissipation in computer systems has resulted in higher cost, lower re- ability, and reduced battery life in portable systems. Consequently, power and energy have become ?rst-class constraints at all layers of modern computer s- tems. PACS 2004 is the fourth workshop in its series to explore techniques to reduce power and energy at all levels of computer systems and brings together academic and industry researchers. The papers in these proceedings span a wide spectrum of areas in pow- aware systems. We have grouped the papers into the following categories: (1) microarchitecture- and circuit-level techniques, (2) power-aware memory and interconnect systems, and (3) frequency- and voltage-scaling techniques. The ?rst paper in the microarchitecture group proposes banking and wri- back ?ltering to reduce register ?le power. The second paper in this group - timizes both delay and power of the issue queue by packing two instructions in each issue queue entry and by memorizing upper-order bits of the wake-up tag. The third paper proposes bit slicing the datapath to exploit narrow width operations, and the last paper proposes to migrate application threads from one core to another in a multi-core chip to address thermal problems.