Year 4 and After Fielded HPC Multi- and Many-core-based Systems

Transcription

1 Year 4 and After Fielded HPC Multi- and Many-cre-based Systems Mtivatin: Accelerate infusin f new technlgies int n-bard and field-deplyable systems Increase cmputatinal capabilities Speed-up applicatin executin Migrate functinality and enhance missin perfrmance Research Plan: Study perfrmance tradeffs assciated with executing Army-relevant applicatins n emerging technlgies, tradeffs w.r.t. executin time, parallelism (scalability), precisin (accuracy), size, weight, and pwer cnsumptin 1 AHPCRC Annual Review - Stanfrd University - Prject 4-3

2 Technical Apprach Technical Apprach Analyze parallel algrithms related t applicatins f interest t the Army in terms f executin-time perfrmance and scalability n emerging technlgies Identify and evaluate tls fr perfrmance measurement and prgram develpment Prfile applicatins/algrithms in terms f pwer cnsumptin, memry hierarchy ftprint, and sensitivity t precisin Develp mdels fr pwer cnsumptin and methds fr pwer management Estimate weight and size f tactical battlefield cmputer systems 2 AHPCRC Annual Review - Stanfrd University - Prject 4-3

3 Results Preliminary Results Pwer Cnsumptin study using SAR (synthetic aperture radar) cde Stere Matching: perfrmance study f algrithm using simulated annealing vs ne using graph cuts OpenCL vs CUDA: perfrmance study using CUDA and OpenCL prfilers 3 AHPCRC Annual Review - Stanfrd University - Prject 4-3

4 Synthetic Aperture Radar (SAR) Pwer Studies Image Frmatin n SAR Cdes Mimics a large radar antenna by taking multiple small-antenna bservatins while traveling ver/alng the area f interest Can prduce high-reslutin radar images with a manageably small antenna Image Frmatin Recnstructin f a radar image frm multiple SAR bservatins One f the mst cmputatinally-demanding phases f the SAR wrkflw Algrithms frm tw main classes: Furier Transfrm-based Frequency-dmain slutin Lwer quality images Mre stringent measurement cnstraints Backprjectin-based Time-dmain slutin Highly parallelizable Ptentially mre cmpute intensive 4 AHPCRC Annual Review - Stanfrd University - Prject 4-3

5 Pwer Studies n SAR Cdes SAR Perfrmance Studies Mtivatin: Given that SAR Image Frmatin is cmpute intensive and, thus, ptentially pwer hungry When SAR systems are run in pwer-cnstrained envirnments, e.g., UAVs, can runtime OS/applicatin-initiated adaptatin reduce Image Frmatin pwer cnsumptin? What trade-ffs exist between pwer and perfrmance, e.g., time-tslutin, image quality, etc.? Preliminary Study: Single vs. Duble Precisin Gal: Quantify pwer and perfrmance tradeffs between single- and duble-precisin versins f frequency- and time-dmain based SAR Image Frmatin algrithms 5 AHPCRC Annual Review - Stanfrd University - Prject 4-3

6 Pwer Studies n SAR Cdes Target SAR Wrklads HPCS SSCA #3 Benchmark (MATLAB) Frequency-dmain Image Frmatin Funded by DARPA Image Frmatin: 2D Furier Matched Filtering Cmputatinal Cmplexity: O(N 2 ) Data Set: SSCA #3 generated synthetic sensr data (size: 244MB, 488MB) Simple SAR Backprjectin Implementatin (MATLAB) Time-dmain Image Frmatin Funded by AFRL Image Frmatin: Unptimized Backprjectin Cmputatinal Cmplexity: O(N 3 ) AFRL Data Sets: SAR-Based GMTI in Urban Envirnment Challenge Prblem (size: 2.95GB) 2D/3D Imaging GOTCHA Challenge Prblem (size: 146MB per input set) 6 AHPCRC Annual Review - Stanfrd University - Prject 4-3

7 Single vs Duble Precisin Pwer Summary Studies f n Observatins SAR Cdes Watt usage: virtually n difference between single- and dubleprecisin Reduced time-t-slutin: main driver f pwer benefits frm singleprecisin runs Energy cnsumptin: Single-precisin prvides significant reductin up t 50.8% Image prcessing similarity metrics cincide with visual cmparisns f SAR single/duble precisin utput 7 AHPCRC Annual Review - Stanfrd University - Prject 4-3

8 Results Preliminary Results Pwer Cnsumptin study using SAR (synthetic aperture radar) cde Stere Matching: perfrmance study f algrithm using simulated annealing vs ne using graph cuts OpenCL vs CUDA: perfrmance study using CUDA and OpenCL prfilers 8 AHPCRC Annual Review - Stanfrd University - Prject 4-3

9 Stere Matching Prblem One f the mst intensely investigated and challenging research prblems in cmputer visin: Cmpute the disparity map given the left and right 2D images then generate the 3D image given the disparity map, which has sufficient infrmatin Skip technical details Perfrmance cmparisn: ARL simulated annealing-based algrithm vs an algrithm using graph cuts Advantages f using graph cuts: integer rather than flating-pint peratins shrter executin time and ptential pwer savings 9 AHPCRC Annual Review - Stanfrd University - Prject 4-3

10 Simulated Annealing vs Graph Cut Summary f Observatins & Future Wrk Summary f Observatins Graph Cut cde succesfully prcessed full and sub-sectin images Graph Cut executed 8 t 14 times faster than Simulated Annealing fr a variety f image inputs Future Wrk Cmpare full-image utput between Simulated Annealing and Graph Cut Analyze pwer cnsumptin savings frm integer-based Graph Cut Imprve energy functin used in cdes while maintaining their equivalence (fr apples-t-apples cmparisn) 10 AHPCRC Annual Review - Stanfrd University - Prject 4-3

11 Results Preliminary Results Pwer Cnsumptin study using SAR (synthetic aperture radar) cde Stere Matching: perfrmance study f algrithm using simulated annealing vs ne using graph cuts OpenCL vs CUDA: perfrmance study using CUDA and OpenCL prfilers* * A detailed reprt f the experimental data is available at: pencl_reprt.dcx 11 AHPCRC Annual Review - Stanfrd University - Prject 4-3

12 Stere Matching OpenCL vs CUDA Mtivatin: OpenCL enables increased prgrammer prductivity due t being a crss-vendr standard fr hetergeneus cmputing. It runs n CUDA-enabled GPUs, sme ATI GPUs, multi-cre prcessrs such as the AMD Phenm TM II x4 prcessr, and ther prcessrs such as the Cell Bradband Engine. Questin: Fr the NVIDIA GPUs, are there perfrmance tradeffs invlved in using OpenCL cmpared t using CUDA? Objective: Cmpare the perfrmance, in terms f executin time and pwer cnsumptin, f cdes cmpiled with CUDA and OpenCL 1.0 with default ptimizatins 12 AHPCRC Annual Review - Stanfrd University - Prject 4-3

13 OpenCL vs CUDA Experimental Stere Matching Methdlgy Cdes: Naïve implementatin f kernels fr the fllwing applicatins, i.e., the implementatin is dne by prting serial cdes t CUDA and OpenCL while fully expressing the available data-parallelism withut using any ptimizatins, e.g., memry calescing, use f shared, texture, and cnstant memry. Matrix Multiplicatin (MM) Matrix Transpse (MT) Dt Prduct f Vectrs (DV) Separable Cnvlutin (SC) Experimental Setup; Each kernel is executed with fur different prblem sizes and the executin time, executin prfile, and pwer cnsumptin are recrded. Fr each kernel and each prblem size tw versins f the cde are run: ne cnsists f a single iteratin f the kernel and the ther cnsists f multiple iteratins. Single iteratin versins are used fr cllecting executin prfiles. Multiple iteratin versins are used fr measurement f pwer cnsumptin and executin time. 13 AHPCRC Annual Review - Stanfrd University - Prject 4-3

14 Cmparisn f Results with Data Stere frm Recent Matching Publicatin Publicatin: Kazuhik Kmatsu, Katsut Sat, Yusuke Arai, Kentar Kyama, Hiryuki Takizawa, and Hiraki Kbayashi, Evaluating Perfrmance and Prtability f OpenCL Prgrams, iwapt Wrkshps, Agreement CUDA and OpenCL cmpilers have different ptimizatin capabilities CUDA cmpiler is mre mature in terms f ptimizatin by default Disagreement In their study, CUDA utperfrmed OpenCL fr every applicatin, while in ur study, OpenCL utperfrmed CUDA nly fr Separable Cnvlutin Pssibly because f different GPU hardware (urs: Tesla C870 and theirs Tesla C1060). 14 AHPCRC Annual Review - Stanfrd University - Prject 4-3

15 Relevance t Army and Research Prtfli - 2 SWaP Cnstraints Fr sme military cmputers executin-time perfrmance is nt enugh. In additin t executin-time perfrmance, field-deplyable and n-bard cmputing systems must satisfy SWaP cnstraints, i.e., Size, Weight, and Pwer cnstraints, as well as envirnmental cnstraints. Field-deplyable Cmputer System Designed fr high perfrmance and server cmputing in a theater f war. On-bard r Battlefield Cmputer System Designed fr highly mbile and rbust battlefield cmmunicatins and telecmmunicatins. Can reside in a small prtable shelter such as a tank r trailer. Can reside in small prtable spaces such as backpacks and clthing, r n an airplane r hummer. 15 AHPCRC Annual Review - Stanfrd University - Prject 4-3

16 Relevance t Army and Research Prtfli - 3 HPC capability in the guise f multi-cre prcessrs, GPUs, FPGAs, acceleratrs and slid-state devices is prpelling the grwth f nntraditinal HPC areas, i.e., n-bard sensr, signal, and image prcessing, t supprt the warfighter. As n-bard systems becme mre capable, applicatins will migrate frm field-deplyable t n-bard systems, and the cmmunicatin between the tw may decrease. This als has ramificatins w.r.t. pwer, executin time, and capability. 16 AHPCRC Annual Review - Stanfrd University - Prject 4-3

17 Relevance t Army and Research Prtfli - 4 Applicatin Segment t Architecture Mapping Given an applicatin segment, identify the best architecture that satisfies SWAP+ cnstraints, while prviding best applicatin perfrmance under these cnstraints. This invlves tradeffs and ptimizatins, e.g., Useful fr Increased parallelism can lead t decreased executin time but increased size, weight, and pwer Large memry ftprints can result in high pwer cnsumptin and larger size and weight Integer, in lieu f flating-pint peratins, can reduce pwer cnsumptin but may nt prvide necessary accuracy/precisin Data structures and algrithms may have t be ptimized fr applicatins t run well n emerging technlgies Chice f cmpilers and cmpiler ptimizatins can affect executin-time perfrmance and pwer cnsumptin Deplyable systems research Determining whether r nt t invest time in, e.g., GPU applicatin develpment Wrklad distributin in hetergeneus cmputing envirnments 17 AHPCRC Annual Review - Stanfrd University - Prject 4-3

18 Pints f Cntact at US Army Research Labratry Aberdeen Prving Grund: Dale Shires, Sng Park, James Rss, Advanced Cmputing and Cmputatinal Sciences Divisin Adelphi Labratry Center: Army Cllabratins Lam Nguyen, Sensrs and Electrn Devices Directrate Andres Sullivan, Sensrs and Electrn Devices Directrate Yansen Wang, Cmputatinal and Infrmatin Sciences Directrate (CISD), Battlefield Envirnment Divisin, Atmspheric Dynamics Branch White Sands Missile Range, CISD, Battlefield Envirnment Divisin: Dn Hck, Chief, Atmspheric Dynamics Branch David Knapp, Chief, Atmspheric Mdeling Applicatin Branch Rbert Dumais at Army: Jhn Ksinski, FIEEE Principal Deputy, Technlgy Intelligence and Infrmatin Warfare Directrate, US Army RDECOM CERDEC 12WD, Frt Mnmuth, NJ 18 AHPCRC Annual Review - Stanfrd University - Prject 4-3

19 Relevance t Cmputatinal Sciences and HPC Cntemprary multiprcessr (MP) systems are hetergeneus in the sense that they are cmprised f multi- and many-cre prcessrs, including acceleratrs, e.g., GPUs. High utilizatin and perfrmance f such systems requires applicatint-architecture mappings and architecture-specific ptimizatins. Pwer cnsumptin is a critical issue fr tday s MP systems, thus, pwer management is an imprtant field f research. 19 AHPCRC Annual Review - Stanfrd University - Prject 4-3

20 Deliverables per APP at Full Funding Green: in prgress preliminary results presented Red: cmpleted links in quarterly reprts Blue: nt started Perfrmance Prfiling (executin time, parallelism, precisin, and pwer) f 2-3 applicatins/algrithms executed n 2-3 technlgies Pwer cnsumptin studies n different technlgies, including flating-pint vs integer cmputatins (useful fr deplyable systems research) Perfrmance Enhancement (applicatin ptimizatin) via perfrmance tls, cmpilers, and cmpiler ptimizatin Cmparative study f OpenCL vs Cuda C Reprt n GPU perfrmance tls Perfrmance enhancement f 2-3 algrithms related t stere matching and SAR Analytical mdeling f GPU perfrmance Applicatin Segment t Architecture Mapping Survey f related literature and preliminary experimentatin Survey f related cde analysis tls Cde analysis f passive stere matching cde Cmparative study f Rfline Mdel and ther related perfrmance mdeling techniques and tls Parallel executin time mdel fr GPUs (useful fr determining whether r nt t invest time in GPU applicatin develpment and fr wrklad distributin) Pwer Management Survey f related literature Discntinued Tasks: Signature-phase related wrk (lcatin f unsupprted Master s student is a mystery) and FPGA- and related wrk (NMSU s fcus) nt yet apprved fr deletin New Task: Develp re-usable, mdular, fast backprjectin cde mdules (New requesting mdificatin t APP) 20 AHPCRC Annual Review - Stanfrd University - Prject 4-3