IPSJ SIG Technical Report Vol.2015-HPC-150 No /8/6 I/O Jianwei Liao 1 Gerofi Balazs 1 1 Guo-Yuan Lien Prototyping F

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I/O Jianwei Liao 1 Gerofi Balazs 1 1 Guo-Yuan Lien 1 1 1 1 1 30 30 100 30 30 2 Prototyping File I/O Arbitrator Middleware for Real-Time Severe Weather Prediction System Jianwei Liao 1 Gerofi Balazs 1 Yutaka Ishikawa 1 Guo-Yuan Lien 1 Takemasa Miyoshi 1 Shigenori Otsuka 1 Hirofumi Tomita 1 Seiya Nishizawa 1 Abstract: A high-resolution 30-minute numerical weather prediction system, using weather observable data that is available every 30 seconds, is being developed. In this system, 100-case ensemble simulations and data assimilation of results and observed data are performed every 30 seconds to predict 30 minute weather. Because the simulation and data assimilation programs are independently developed, data is exchanged via files. In this paper, after examining a mechanism to recycle two application jobs, an efficient data transfer method between application processes is designed, implemented and evaluated. 1. 30 30 [1], [2] *1 30 i) 100 ii) 30 3 8 9 2 30 iii) 30 1 *1 CREST I/O I/O RDMA (Remote Direct Memory Access) [2], netcdf API[3] 100 netcdf API MPI 1

(a) (b) 1 1.1 2. 1(a) 30 30 LES SCALE[4] NHM 100 100 100 LETKF [5] [6] 30 3 (37.6MB/parameter) 100 30 MPI 100 120 Km x 120 Km 80 16 13.7GiB 1200 1200 80 16 8Byte = 13.7GiB 100 1.3TiB ( 1(b)) MPI MPI MPI 1:N:1 SCALE I/O netcdf[3] LETKF 2.1 2.2 2

100 x 80 100 x 80 100 100 0 99 2 3 2.1 180 18,000 100 18,000 2 100 2 1 1 1 180 1200 x 1200 180 1 100 x 80 80 80 16 8Byte = 819 KB 100 100 x 80 100 100 100 x 80 100 2 2.2 100 (180 x100) 18,000 2 100 x 80 3 3 100 x 80 3 0 100 100 100 2 100 x 80 100 100 100 3. netcdf API ( 1 ) 3 ( 2 ) ( 3 ) 30 3

4 01: /* Initialization */ 02: 03: nc_create("data1.nc", ncmode, &ncid1); 04: nc_create("data2.nc", ncmode, &ncid2); 05: /* Another Initialization **/ 06: /* main computation */ 07: /* data output */ 08: for (i = 0; i < 2; i++) 09: nc_put_vara(ncid, vid[i], startp, countp, buf+i*n); 10: for (i = 0; i < 2; i++) 11: nc_put_vara(ncid, vid[i], startp, countp, buf+i*n); 12: nc_close(ncid1); 13: nc_close(ncid2); 14: 15: 16: /* Finalization */ 5 3.1 2 MPI MPI Comm Accept MPI Comm Connect 4 128 4 30 3.2 01: /* Initialization */ 02: while(1) { 03: nc_create("data1.nc", ncmode, &ncid1); 04: nc_create("data2.nc", ncmode, &ncid2); 05: /* Another Initialization **/ 06: /* main computation */ 07: /* data output */ 08: for (i = 0; i < 2; i++) 09: nc_put_vara(ncid, vid[i], startp, countp, buf+i*n); 10: for (i = 0; i < 2; i++) 11: nc_put_vara(ncid, vid[i], startp, countp, buf+i*n); 12: nc_close(ncid1); 13: nc_close(ncid2); 14: 15: } 16: /* Finalization */ 6 5 netcdf 3 4 nc create 9 11 nc put vara 12 13 nc close nc create 6 3 13 1 4 5 6 nc create nc create nc create netcdf netcdf nc create netcdf next cycle 6 14 next cycle netcdf File I/O nc create, nc open NC COMM NC COMM nc create MPI API MPI Comm Accept nc open MPI API MPI Comm Connect 2 4

7 MPI 9 File I/O /* Simulator */ nc_create(...); nc_def_dim(...); nc_def_var(...); nc_put_var_double(...); nc_close() /* Assimilation */ nc_open(...); nc_inq_dimid(...); nc_inq_varid(...); nc_get_var_double(...); nc_close(...); 8 3.3 netcdf API MPI Two sided MPI MPI MPI 7 OSU osu bw Two sided 3 I/O MPI Two sided 8 nc put var double nc get var double 9 819KB X Y 128 13.6 32 128 4 4. netcdf API MPI Two sided netcdf 2 netcdf netcdf RDMA I/O CREST [1] Balazs, G. Vol. 2014-HPC-143(2), pp. 1 6 (2014). [2] Balazs, G. Lien, G.-Y. I/O 5

Vol. 2014-HPC-143(2), pp. 1 6 (2014). [3] Li, J., Liao, W.-k., Choudhary, A., Ross, R., Thakur, R., Gropp, W., Latham, R., Siegel, A., Gallagher, B. and Zingale, M.: Parallel netcdf: A High-performance Scientific I/O Interface, Supercomputing, 2003 ACM/IEEE Conference, IEEE, pp. 39 39 (online), available from http://www.ece.northwestern.edu/ choudhar/publications/lilia03a.pdf (2003). [4] Tomita, H.: SCALE-LES: Strategic development of large eddy simulation suitable to the future HPC, Solution of Partial Differential Equations on the Sphere (2012). [5] Takemasa, Miyoshi, Yamane, S. and Enomoto, T.: Localizing the Error Covariance by Physical Distances within a Local Ensemble Transform Kalman Filter (LETKF), Scientific Online Letters on the Atmosphere (SOLA), Vol. 3 (2007). [6] Ushio, T., Wu, T. and Yoshida, S.: Review of Recent Progress in Lightning and Thunderstorm Detection Techniques in Asia, Atmospheric Research, Vol. 154, pp. 89 102 (2015). 6