A FAST HEURISTIC FOR TASKS ASSIGNMENT IN MANYCORE SYSTEMS WITH VOLTAGE-FREQUENCY ISLANDS

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1 Shervn Haamn A FAST HEURISTIC FOR TASKS ASSIGNMENT IN MANYCORE SYSTEMS WITH VOLTAGE-FREQUENCY ISLANDS INTRODUCTION Increasng computatons n applcatons has led to faster processng. o Use more cores n a chp wth more parallelsm. These applcatons are typcally composed of phases wth dfferent computaton/memory access characterstcs. Chp-wde voltage/frequency settng does not address applcatons wth varable computatons. 2

2 INTRODUCTION Power/Energy-aware methods have to mantan reasonable power budget wth ncreasng the number of cores n a sngle chp. Voltage Frequency Islands (VFI) o Multcore system s parttoned nto slands. o Adust the slands voltage/frequency levels to reduce system energy consumpton wthn a desred performance penalty. 3 ISLANDING Fne-gran to coarse-gran o Tradeoff aggressve energy savng vs hardware desgn smplcty and cost Core VFI VFI 2 VFI 3 VFI 4 4 2

3 WORKLOAD BALANCE (PER VFI) In an sland cores may have dfferent computaton worloads. Increasng or decreasng the V/F level of such an unbalanced sland consumes extra energy or delays the executon tme of applcaton. VFI Core V/F hgh Core 2 Tass Extra energy VFI Core V/F low Core 2 Tass Extra delay 5 RESEARCH MOTIVATION Address manycore energy effcency on a symmetrc VFI archtecture o Optmze tas-to-sland assgnments (tas parttonng) o Optmze V/F level assgnments for slands V/F levels are dynamcally assgned per executon phase of applcatons Optmzaton obectve o Mnmze applcaton executon tme (maespan) wthout volatng energy consumpton budget. 6 3

4 RELATED WORK Research wors that utlze VFIs for energy effcency fall n one or more of the followng categores: o Desgn-tme (statc) vs. runtme (dynamc) optmzaton. [ref] o Symmetrc vs. non-symmetrc VFIs. [ref] o Solve slandng and V/F level assgnment sub-problems smultaneously or ndvdually. [ref] o Improve the energy effcency of VFI-based system w/o consderng the smlartes of worloads of cores. [ref] o Provde exact or (meta) heurstc solutons to solve the VFI s sub-problems. [ref] 7 RELATED WORK (CONT.) Closely related wors o K. Durasamy et al. Energy Effcent MapReduce wth VFIenabled Multcore Platforms DAC 205. o R. Km et al. Wreless NoC and Dynamc VFI Codesgn: Energy Effcency Wthout Performance Penalty IEEE TVLSI 206. o S. Pagan et al. Energy Effcent Tas Parttonng based on the Sngle Frequency Approxmaton Scheme IEEE RTSS

5 SYSTEM MODEL N N multcore system (N s the number of cores) System s composed of VFIs that each assocates wth a V/F par N N 9 TASK EXECUTION MODEL Benchmars o Mult-threaded worloads executed on a dstrbuted shared memory platform. o The performance of our proposed methodology s optmzed usng data collected from worload s parallel secton (regon of nterest). Executon phase o The parallel secton conssts of a sequence of executon phases. o The executon phases are separated by synchronzaton functon calls (locs and barrers). 0 5

6 TASK EXECUTION MODEL (CONT.) TASK EXECUTION PROFILES The tas set of each benchmar s run multple tmes each tme wth a fxed V/F level for the entre executon run. For each tas three parameters are profled o Executon tme o Energy consumpton o Worload/Utlzaton Statcally use ths profle to optmze the tasto-sland and dynamc V/F level assgnments. 2 6

7 CONTRIBUTION Two-step optmzaton framewor for mnmzng maespan gven an energy budget for symmetrc VFIs. o Formulate the tas-to-sland assgnment problem usng mxed nteger lnear programmng. o Formulate the dynamc V/F level assgnment problem for the VFIs usng nteger lnear programmng. Propose a fast heurstc that obtans nearoptmal solutons for solvng the tas-to-sland assgnment problem. 3 CONTRIBUTION (CONT.) Evaluate the optmzaton framewor on benchmars wth dfferent computatonal characterstcs. Compare the energy effcency of proposed framewor to optmal per-core VFIs. o Use Energy-Delay Product (EDP) and IPS 2 /Watt as well-nown performance metrcs. 4 7

8 8 TASK-TO-ISLAND ASSIGNMENT Identfy and group tass wth smlar worloads. Defne smlarty measure based on the dfference between the tas worload and the maxmum worload n a gven executon phase. 5 TASK-TO-ISLAND ASSIGNMENT PROBLEM FORMULATION 6 Descrpton Formulaton Obectve Mnmze the wasted worload per phase. Constrant s Compute the wasted worload for a tas. Approxmate the maxmum worload and ts recprocal. Determne one of the tass n the phase as the one wth the maxmum worload. A tas s assgned to only one sland. All slands have the same number of tass (symmetry of slands). Compute the probablty of approxmatng the maxmum worload wth a lne segment. T T y Y Mnmze N K x z c F y I T F t x y I z a c r I z a F r I T c x t I z I Q x T x r K K

9 DYNAMIC V/F LEVEL ASSIGNMENT An Island may have dfferent amounts of worloads across executon phases. Changng the V/F levels of the slands helps ncrease energy savng and performance. o Speed up slands wth hgh worloads. o Slow down slands wth low worloads. V/F levels: s < s 2 < s 3 < s 4 7 DYNAMIC V/F LEVEL ASSIGNMENT FORMULATION Obectve Constrant s Descrpton Mnmze the maespan. Compute the length of an executon phase after assgnng the V/F levels of slands. Only one V/F level s assgned to an sland n a gven executon phase. The energy consumpton of system s below the pre-defned energy budget. Formulaton L l Mnmze a l d l a l L l a l P I T T I T T P K L e l a l EB EB l 0 8 9

10 FAST HEURISTIC FOR TASK-TO-ISLAND ASSIGNMENT Tass are sorted by ther worloads (O(N log(n)) Sorted tass are assgned to slands (O()) The heurstc solutons are very close to the MILP-based solutons. After applyng heurstc Before applyng heurstc τ τ τ 2 τ 3 τ 4 τ 4 τ 2 τ3 Core Core 2 Core 3 Core 4 VFI VFI 2 9 SIMULATION SETUP We use GEM5 as a full system smulator to obtan processor-level performance nformaton. Processor-level statstcs generated by GEM5 smulatons are fed to McPAT (Mult-core Power Area and Tmng). McPAT generates processor-level power/energy statstcs. Voltage (V)/Frequency (GHz) levels Processors 64 Alpha cores L-cache 64Byte 4-way assocatve 64 Byte L2-cache Man memory Processor confguraton Shared 8 MBytes 8-way assocatve 64 Byte 28KBytes dstrbuted per core 52 MBytes 20 0

11 BENCHMARKS Three applcatons from SPLASH-2 and PARSEC benchmar sutes are consdered n our smulatons. Benchmar Problem sze Applcaton doman FFT Data Ponts Fast Fourer Transform LU CANNEAL 52x52 Matrx 6x6 Blocs Elements Dense matrx computaton Mnmze routng cost n chp wth smulated annealng 2 VFIS CONFIGURATIONS Implemented the heurstc n MATLAB. Modeled the problem formulatons n AMPL. o Used Gurob to solve the problem. Symmetrc VFIs: 4 VFIs 6 cores per VFI. 22

12 RESULTS Compare the proposed Dynamc Coarse-Gran (DCG) VFIs aganst optmal Fne-Gran (FG) VFIs. o Executon tme o Energy effcency Compare V/F level dstrbutons for VFIs across the benchmars. 23 PERFORMANCE EVALUATION Compare the executon tmes of FG and DCG o Energy budget o Computaton ntensveness of benchmars Three energy budgets (EB) that reduce cores hghest energy usage by o a) 7.5% EB(H) o b) 22.5% EB(M) o c) 37.5% EB(L) 24 2

13 PERFORMANCE EVALUATION (EXECUTION TIME) 25 PERFORMANCE EVALUATION (ENERGY EFFICIENCY) 26 3

14 PERFORMANCE EVALUATION (V/F LEVEL DISTRIBUTIONS) Percentage of V/F levels assgned to Benchma r s VFIs s 2 s 3 s 4 FFT LU CANNEAL REAL-WORLD APPLICATION OF THE OPTIMIZATION FRAMEWORK Use for ernel applcatons wth moderate worload varatons across executon phases. Optmze the tas and V/F level assgnments once at comple-tme. Store optmzaton outcomes and use them many tmes whle runnng the applcatons. 28 4

15 CONCLUSION Proposed a two-step optmzaton framewor for mnmzng maespan whle mantanng energy consumpton below pre-defned budget. Proposed a fast heurstc for balancng the computatonal worload of each sland per executon phase. Evaluated the performance of framewor aganst the optmal per-core VFIs as well as on dfferent compute-ntensve benchmars. 29 5