Advanced Profiling of GROMACS
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1 Advanced Profiling of GROMACS Jesus Labarta Director Computer Sciences Research Dept. BSC All I know about GROMACS A Molecular Dynamics application Heavily BSC Not much Courtesy Modesto Orozco,(BSC) Jesus Labarta. NSC 09 October
2 My interest Efficiency? Scalability? Can it be improved? Test case for our CEPBA-Tools environment Feedback/drive or research Performance analysis tools Programming models Automatic Load balancing Interconnects Nucleosome test case atoms TIP3P water model parmbsc0 force-field Berendsen thermostat and barostat, 2 fs time step constraints on Hydrogens Courtesy Agnes Noy (UB) Jesus Labarta. NSC 09 October Evaluation infrastructure XML control Valgrind OMPITrace MRNET Dyninst, PAPI.prv Valgrind instrumentation Time Analysis, filters.prv +.pcf Paraver.cfg.trf DIMEMAS VENUS (IBM-ZRL) how2gen.xml Dimemas Venus integration Stats Gen.viz.cube.xls.txt Machine description Instr. Level Simulators PeekPerf Data Display Tools Jesus Labarta. NSC 09 October
3 Index A story on Performance for (;;) Parallel efficiency Sequential performance (, ) Hybrid programming Jesus Labarta. NSC 09 October Performance Raw user metric (ns/day) NAMD 2.7 GMX4_mn_work_nucleo_nsd ay GMX4_mn_stop_nucleo_nsd ay GMX4_cluster_work_nsday Jesus Labarta. NSC 09 October
4 Problems? Measured Procs phase eff 64 all 0,55 64 FFTs 0,55 64 Particles 0, all Particles FFTs 0.29 Not really good Bad!!! Usual suspects Lot of communication, large messages, Jesus Labarta. NSC 09 October Parallel efficiency Jesus Labarta. NSC 09 October
5 Lots of communications, message sizes, Suspect convicted? Particles FFTs MPI Call Recv sendrec Allreduce Message Size 4 KB 40KB 80KB Jesus Labarta. NSC 09 October Convicted Who? Machine? Program? Average Bandwidth per core? MB/s Ideal interconnect Measured Prediction ideal Procs phase eff 64 all 0,55 64 FFTs 0,55 64 Particles 0, all Particles FFTs all Particles FFTs 0.52 Better!!!!!! Not that good!!!!!! Jesus Labarta. NSC 09 October
6 Sensitivity to interconnect parameters Measured Prediction ideal Procs phase eff 64 all 0,55 64 FFTs 0,55 64 Particles 0, all Particles FFTs all Particles FFTs 0.52 time latency impact for different bandwidths (MB/s) 0,14 0,12 0,1 0,08 0,06 0,04 0, latency Bandwidth impact for different latencies (us) Latency. Need to group messages? Sensitivity to network bandwidth? Time 0,5 0,45 0,4 0,35 0,3 0,25 0,2 0,15 0,1 0, Bandwidth (MB/s) Jesus Labarta. NSC 09 October Jesus Labarta. NSC 09 October
7 Not as much gain as expected??? Particles FFTs No Jesus Labarta. NSC 09 October Histogran of duration: Not uniform impact!!!! Across Particle processes Between FFTs and Particles FFTs Particles FFTs No Jesus Labarta. NSC 09 October
8 Histograms of Instructions Particles FFTs No Jesus Labarta. NSC 09 October 2009 waterbox Impact depends on actual data!!! No No Jesus Labarta. NSC 09 October
9 Back to parallel performance Jesus Labarta. NSC 09 October Performance factors TotalLB Parallel _ η = LB * microlb* Transfer η = Parallel _η * relipc * Comp Comm Performance Factors 1,2 1 0,8 0,6 0,4 0,2 Parallel_Ef f LB Comm rel IPC Comp ulb Transfer Total LB Efficiency Processors Jesus Labarta. NSC 09 October
10 Structure: A few colors MPI call FFTs User FFTSs recv sendrec allreduce make_bsplines gather_f_bsplines solve_pme MPI call Particles recv sendrec User Particles ewald_lrcorrection do_nonbonded Jesus Labarta. NSC 09 October Scaling structure User Particles User FFTSs Jesus Labarta. NSC 09 October
11 PRACE Test case Useful Duration MPI calls Particles FFTs Average point to point bandwidth: 13 MB/s Jesus Labarta. NSC 09 October PRACE Test case Effects opportunities Instructions Duration Particles FFTs Jesus Labarta. NSC 09 October
12 Back to sequential performance Jesus Labarta. NSC 09 October processes: FFTs Globally balanced but some local imbalance Imbalance Imbalance Jesus Labarta. NSC 09 October
13 Online analysis Nucleosome Jesus Labarta. NSC 09 October Online analysis PRACE Test case (two versicles) Similarities / differences / opportunities (??) Jesus Labarta. NSC 09 October
14 Detailed metrics Application characterization Metric Description Cluster 1 Cluster 2 Cluster 3 Cluster 4 FMA ops per floating point instruction PM_FPU_FMA / PM_FPU0_FIN + PM_FPU1_FIN Instructions per Load/Store PM_INST_CMPL / (PM_LD_REF_L1 + PM_ST_REF_L1) HW floating point instructions (flips) PM_FPU0_FIN + PM_FPU1_FIN Total floating point operations (flops) PM_FPU0_FIN + PM_FPU1_FIN + PM_FPU_FMA - PM_FPU_STF Total FP Load&Store operations (fp_tot_ls) PM_LSU_LDF + PM_FPU_STF FMA % 2 * PM_FPU_FMA / flops Memory Mix (PM_LD_REF_L1+ PM_ST_REF_L1) / PM_INST_DISP Load Mix PM_LD_REF_L1 / PM_INST_DISP Store Mix PM_ST_REF_L1 / PM_INST_DISP FPU Mix flips / PM_INST_DISP FXU Mix PM_FXU_FIN / PM_INST_DISP 0,681 0,768 0,700 0,436 1,470 1,465 1,659 1, ,51% 44,12% 37,19% 81,21% 32,61% 24,70% 30,26% 25,20% 25,83% 19,39% 24,93% 24,76% 6,77% 5,32% 5,32% 0,44% 1,06% 8,22% 2,00% 5,32% 20,85% 16,19% 24,38% 16,07% Jesus Labarta. NSC 09 October Detailed metrics Behavior on architecture Metric Description Cluster 1 Cluster 2 Cluster 3 Cluster 4 % Instr. Completed PM_INST_CMPL / PM_INST_DISP 47,93% 36,20% 50,21% 32,90% L1 misses per Kinstr. (PM_LD_MISS_L1 + PM_ST_MISS_L1 / PM_INST_CMPL) * ,18 37,04 10,38 63,81 L2 misses per Kinstr. (PM_DATA_FROM_MEM / PM_INST_CMPL) * ,093 0,103 0,057 1,008 Bytes from maim memory per floating point instruction finished (PM_DATA_FROM_MEM * mem_line_size) / PM_FPU_FIN 0,084 0,090 0,068 9,712 Number of Loads per Load miss PM_LD_REF_L1 / PM_LD_MISS_L1 121,81 74,99 102,29 11,84 Number of Stores per Store miss PM_ST_REF_L1 / PM_ST_MISS_L1 24,53 4,91 19,19 50,31 Number of Loads&Stores per L1 miss (PM_LD_REF_L1 + PM_ST_REF_L1) / (PM_LD_MISS_L1 + PM_ST_MISS_L1) 66,80 18,42 58,05 12,00 L1 cache hit rate 1 - (PM_LD_MISS_L1 + PM_ST_MISS_L1) / (PM_LD_REF_L1 + PM_ST_REF_L1) 98,50% 94,57% 98,28% 91,67% Number of Loads per (D)TLB miss PM_LD_REF_L1 / PM_DTLB_MISS , , , ,87 Number of Loads&Stores per (D)TLB miss (PM_LD_REF_L1 + PM_ST_REF_L1) / PM_DTLB_MISS , , , ,36 % TLB misses per cycle PM_DTLB_MISS / PM_CYC 0,000% 0,000% 0,000% 0,001% Total Loads from local L2 (M) (total_ld_l_l2) PM_DATA_FROM_L2 / 1024*1024 0,173 0,060 #VALUE! 0,381 Local L2 load traffic (MB) L1_cache_line_size * total_ld_l_l2 22,126 7,635 #VALUE! 48,781 Jesus Labarta. NSC 09 October
15 Detailed metrics Real Performance Metric Description Cluster 1 Cluster 2 Cluster 3 Cluster 4 % Duration Avg. Burst Duration (μs) , , , ,58 Total preemted time (μs) Avg. Burst Duration (PM_CYC * processor_cycle_time) % preempted time Preempted Time / Avg. Burst Time IPC PM_INST_CMPL / PM_CYC CPI 1/IPC MIPs PM_INST_CMPL / Avg. Burst Duration Mem.BW (MB/s) (PM_DATA_FROM_MEM * mem_line_size ) / Avg. Burst Duration Memory instructions per second (PM_LD_REF_L1 + PM_ST_REF_L1) / Avg. Burst Duration HW floating point instructions per cycle flips / PM_CYC Flop rate (MFLOPs) flops / Avg. Burst Duration HW floating point instructions rate flips / Avg. Burst Duration Computation intensity flops / fp_tot_ls Local L2 load bandwidth per processor (MB/s) L1_cache_line_size * total_ld_l_l2 / Avg. Burst Duration % Loads from local L2 per cycle PM_DATA_FROM_L2 / PM_CYC 366,81 123,88 576,02 75,37 1,725% 1,503% 1,574% 1,302% 1,11 0,68 1,08 0,69 0,90 1,46 0,93 1, , , , ,34 29,74 20,43 17,60 202, , , , ,69 0,024 0,155 0,043 0,112 67,55 482,72 176,45 585,70 55,24 351,40 96,97 253,16 1,065 1,323 1,767 1, ,72 926,19 #VALUE! 8.424,28 0,378% 0,335% #VALUE! 3,043% Jesus Labarta. NSC 09 October Hybrid MPI + OpenMP Jesus Labarta. NSC 09 October
16 Hybrid parallelization OpenMP parallelization Particles by Christian Simarro (BSC) FFTs by Sebastian von Alfthan (CSC) 256 MPI x 4 openmp 130 procs!!!! Jesus Labarta. NSC 09 October Hybrid parallelization FFTs Partial parallelization Too synchronous MPI OpenMP MPI OpenMP. OS scheduling issues Not Parallelized Jesus Labarta. NSC 09 October
17 Hybrid parallelization Particles for(n=n0; (n<n1); n++) { #pragma omp parallel for private(tabledata, nrnb_ind, nlist, outeriter, inneriter, tabletype, kernelptr) shared(fr,nblists) for(i=i0; (i<i1); i++) { if (something) compute(); } Right place? Very imbalanced Few iterations Big difference across processes Jesus Labarta. NSC 09 October Dynamic Load Balancing run time MPI + OpenMP (StarSs) Job is started with P MPI processes each with 1 OpenMP thread Processes blocking at MPI calls lend cores to other processes 800 cores: Sup=2.5 BT-MZ class 32 way Power6 BT-MZ class 32 way Power6 Outlined routines # treads/proc # MPI Procs Total # used CPUs Jesus Labarta. NSC 09 October
18 Conclusion Applications: Nothing IS, everything CAN BE Can always be different, input data dependent Important to get insight into actual behavior. Need dynamic run time optimization GROMACS: an interesting case Really heterogeneous application Serialization and load balancing issues A target for MPI + SMPSs Automatic Load Balance Overlap communication/computation The need for cooperative work Jesus Labarta. NSC 09 October
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