C++ TPDPL(Template Parallel Distributed Processing Library) C X10 1) Place Activity X10 Place 2) 2.2 C++ C/C++OpenMP MPI C/C++ OpenMP

Transcription

1 C CPU S.C. () PC C++ TPDPL(Template Parallel Distributed Processing Library) PE(Processing Element ) S.C.(T2K ) An Implementation of C++ Task Mapping Library and Evaluation on Heterogeneous Environments Takeo YAMASAKI, 1 Daisuke MIYAMOTO 2 and Masaya NAKAYAMA 2 Modern computing architectures are increasingly parallel distributed. This trend is driven by multi-core processors, grid, cluster and cloud-computing. These systems are complicated because of their scale, heterogeneous structures, and asymmetric architectures. Therefore, more productive paradigm that assists development of parallel distributed processing applications is required and has been considered. In this paper we pay attention to task mapping paradigm, and design C++ parallel distributed programing library, TPDPL (Template Parallel Distributed Processing Library), and develop PE (Processing Element) Containers and task mapping algorithms. Finally we report the performance evaluation of them on T2K open supercomputer and private cluster computer and cloud computer and we confirm the performance of TPDPL task mapping system Graduate School of Engineering, The University of Tokyo 2 Information Technology Center, The University of Tokyo FPGA GPU C GPU C++ C++ OpenMP MPI CORBA C++ C++11 C++ 15

2 C++ TPDPL(Template Parallel Distributed Processing Library) C X10 1) Place Activity X10 Place 2) 2.2 C++ C/C++OpenMP MPI C/C++ OpenMP (Omni OpenMP/S- CASH 3),XcalableMP 4) ) MPI (Grid MPI 5) ) (MPC++ 6) ) TBB 7) 8) 9) 2.3 C++11 C++ 10) thread future promiss async mutex condition variabl atomic operation 3. X10 Place Activity PE (processing element) PE 12) MPC++ PE PE PE, thread pe TCP MPI PE tcp pe mpi pe GPU FPGA PE PE PE 16

3 STL(Standard Template Library) C++ ( 1) STL PE STL vector list PE PE PE PE PE 11)12) PE PE PE PE for 3.1 PE PE PE PE PE PE pe vector PE thread pp, mpi pp, tcp pp PE hetero PE.1 pe vector 1 STL TPDPL std::vector PE talloc join set join set PE id 1 : pe vector 1 int add(int a, int b){ return a+b; } 2 void test(){ 3 // thread pe 4 4 pe vector<thread pe> pevec(4); 5 join set js; 6 for(int i=0; i<4; i++){ 7 js += pevec[i].talloc(add, 1, i); 8 } 9 js.join all(); 10 } PE.2 PE pe vector thread pp CPUID CPU full assign mpi pp MPI CPU thread pe PE 17

4 12 mpi pe slave() tcp pp tcp pe set pe thread pe (23 ) tcp pe full assign assign (10 ) 2 : PE 1 void test(){ 2 // thread pe 3 thread pp tpp; 4 tpp.full assign(); 5 // mpi pe 6 mpi pp mpp; 7 mpp.full assign(); 8 // tcp pe 9 tcp pp spp; 10 spp.assign(64); 11 } 12 void mpi pe slave(){ 13 // MPI 0 14 mpi pe singleton::start server(); 15 while(mpi pe singleton::is server working()){ 16 Sleep(10); 17 } 18 } 19 void tcp pe slave(){ 20 // 21 network tools::init sock(); int port = 50000; 24 tcp pe mta(" ", port); 25 thread pp tpp; 26 tpp.full assign(); 27 for(uint32 t i=0; i<4; i++){ 28 mta.talloc(&tcp pe singleton::set pe, 29 (void )&tpp.at(i)); 30 } 31 mta.talloc(set pes, inst); 32 while(tcp pe singleton::is server working()){ 33 Sleep(10); 34 } 35 } : 1 void test(){ 2 hetero<thread pp, mpi pp, tcp pp> pec; 3 // thread pe CPU 4 pec.get pec0().full assign(); 5 // mpi pe CPU 6 pec.get pec1().full assing(); 7 // tcp pe 64PE 8 pec.get pec2().assign(64); 9 pec.reflush(); hetero<thread pp, mpi pp, tcp pp>::iterator it; 12 for(it=pec.begin(); it!=pec.end(); it++){ 13 it.talloc(/ task /); 14 } 15 pec.join all(); 16 } PE hetero PE.3 PE get pecn N 4 get pec0 thread pp 6 get pec1 mpi pp 8 get pec2 tcp pp PE 12 for begin() end() PE PE thread pp mpi pp tcp pp 3.2 PE PE PE PE PE PE for PE PE 3 PE even CPU clock for 1 test.4 for xxx PE PE talloc 4 : 1 void test(){ 2 thread pp pec; 3 { 4 reducer<int> ret; 5 ret += for even(pec).talloc(load, 1, 10000); 6 ret.jreduce(); // join & reduce 7 } 8 { 9 reducer<int> ret; 10 ret += for clock(pec).talloc(load, 1, 10000); 18

5 11 ret.jreduce(); 12 } 13 { 14 reducer<int> ret; 15 ret += for test(pec).talloc(load, 1, 10000); 16 ret.jreduce(); 17 } 18 } 4. Task Mapping PE 4.1 S.C. HaaS (StarBED 13) ) S.C. T2K Open Supercomputer( ) HA8000 CPU AMD Opteron GHz 4 1 4CPU 4 OS RedHat Enterprise Linux 5, gcc version 4.1.2, MPI ver.1.2 MPICH-MX CPU Intel Xeon W GHz 4 2 OS ubuntu10.04lts, gcc version 4.4.3, MPI MPICH2 StarBED Intel Xeon X GHz 6 2CPU 5 OS Debian gcc PE 128 PE node0 thread pe 4 node1 mpi pe 4 S.C. tcp pe 60 StarBED tcp pe 60 PE S.C. 64 PE 64 tcp pe mpi pe PE StarBED CPU CPU PE OS PE.6 hetero thread pp mpi pp tcp pp2 S.C. TCP file pe NFS node0 tcp pe 1.25GB/s 7.5GB/s StarBED tcp pe JGN-X 14) StarBED 1Gb/s 1Gb/s 2 S.C. StarBED S.C. WAN NFS 5 : PE 1 hetero<thread pp, mpi pp, tcp pp, tcp pp> pec; 2 // thread pe pool CPU (4PE) 3 pec.pec0.full assign(); 4 // mpi pe CPU (4PE) 5 pec.pec1.full assing(); 6 // S.C. 60PE 7 pec.pec2.assign(60); 8 // StarBED 60PE 9 for(int i=0; i<60; i++){ 10 pec.pec2.assign(ip[i], port[i]); 11 } 2 PE 19

6 4.2 (.6) int load int double load double load for 6 : 1 uint64 t load int(int64 t start, int64 t end){ 2 uint64 t a=0; 3 for(uint32 t i=start; i<=end; i++) 4 for(uint32 t j=0; j<=1000; j++) 5 a += (uint64 t)(i+j) (i j) (i j) (i/j); 6 return a; 7 } 8 uint64 t load double(int64 t start, int64 t end){ 9 uint64 t a=0; 10 for(uint32 t i=start; i<=end; i++) 11 for(uint32 t j=0; j<=1000; j++){ 12 double ii=(double)i,jj=(double)j; 13 a += ((jj/ii) (ii jj)/(ii jj) (ii/jj); 14 } 15 return a; 16 } even,clock,test even /68 clock PE */( ) test / /( ) even clock CPU PE CPU test 1 for 3 even,clock,test load int load int node0 node1 S.C. StarBED even 1 S.C. clock CPU test 4 load double double even clock S.C. test test 5 test PE for 1 PE 4 node0 4 node1 60 S.C. 60 StarBED node0 S.C. S.C. 20

7 test PE PE 4 even,clock,test load double StarBED StarBED 5 load double test load double even PE load CPU 5. C++ (TPDPL) S.C. 1) Vijay Saraswat, Bard Bloom, Igor Peshansky, Olivier Tardieu, David Grov: Report on the Programming Language X10 version 2.1, documentation/languagespec/x10-latest.pdf (2011) 2) Yonghong Yan, Jisheng Zhao, Yi Guo, and Vivek Sarkar, Hierarchical Place Trees: A Portable Abstraction for Task Parallelism and Data Movement, Proceedings of the 22nd Workshop on Languages and Compilers for Parallel Computing (LCPC), October ),,,,, :Ethernet OpenMP Omni/SCASH, HPC 2002-HPC pp , ) XcalableMP, ACS Vol.3 No. 3, ( ), , ) Y.Ishikawa, M.Matsuda, T.Kudoh, H.Tezuka, S.Sekiguchi:GridMPI - MPI, SWOPP03, ) Yutaka Ishikawa, Atsushi Hori, Mitsuhisa Sato, Motohiko Matsuda, Jorg Nolte, Hiroshi Tezuka, Hiroki Konaka, Munenori Maeda, Kazuto Kubota :Design and Implementation of Metalevel Architecture in C MPC++ Approach - -, Reflection 96 Conference, April , ) Threading Building Blocks web site, http: //threadingbuildingblocks.org/ (2011) 8),,,. :, 2011-HPC-129, ),,, : 21

8 , 2011-HPC- 129, ) The C++ Standards Committee open-std.org/jtc1/sc22/wg21/ 11), : C++, HPCS2011 IPSJ Symposium Series, Vol.2011, p.82 (2011) 12) :C++ tpdplib T2K NPB, HPC-129, No.26, ) StarBED Project 14) JGN-X ( ) 2011 ( ) ( ) 1986,.. ( )... IEEE,, 22