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Biryaltsev E.V., Galimov M.R., Demidov D.E., Elizarov A.M. HPC CLUSTER DEVELOPMENT AND OPERATION EXPERIENCE FOR SOLVING THE INVERSE PROBLEMS OF SEISMIC.

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Presentation on theme: "Biryaltsev E.V., Galimov M.R., Demidov D.E., Elizarov A.M. HPC CLUSTER DEVELOPMENT AND OPERATION EXPERIENCE FOR SOLVING THE INVERSE PROBLEMS OF SEISMIC."— Presentation transcript:

1 Biryaltsev E.V., Galimov M.R., Demidov D.E., Elizarov A.M. HPC CLUSTER DEVELOPMENT AND OPERATION EXPERIENCE FOR SOLVING THE INVERSE PROBLEMS OF SEISMIC PROSPECTING

2 HPC - INDUSTRIAL DEPLOYMENT 2 MASS MARKET READY

3 OIL & GAS INDUSTRY AND TECHNOLOGY REPLACEMENT 3 NEW SOLUTIONS REQUIRED PRICE DROP PRODUCTION & EXPLORATION COMPLEXITY

4 NUMERICAL SIMULATION 4 GRID SIMULATION METHODS

5 FULL WAVE INVERSION 5

6 LOW-FREQUENCY SEISMIC SOUNDING (LFS) 6

7 APPLICATIONS 7 1.Oil & gas prospecting 2.Fracturing control 3.Borehole environment monitoring

8 REQUIREMENTS 8 ACCESSIBILITY BIG DATA ARRAYS PERFORMANCE VISUALIZATION 30 000 models per cycle 10 9 – 10 12 cells ~1 Tb per model

9 RESEARCH & DEVELOPMENT 9 1. The best performance for the massive parallelism tasks. 2. High computation density per equipment units. 3. Perspective technology. GPU — EFFICIENT CHOICE

10 GPU CLUSTER 10 UPS Eaton 9155 Power Rating 8000 / 7200 (VA/Watts) 0.7 Power factor Server >80 Tb Data storage space + SSD cache Virtualization server Citirix XenServer platform 2 x NVIDIA GK104GL with NVIDIA GRID K2 technology Mellanox InfiniBand network switch 56 Gbit/s 6 GPU cluster nodes 4 x AMD FirePro W9100 (16Gb GDDR5, 5.24 Tflops peak) 2 x Intel Xeon E5-2643 v2 (25M cache, 3.50 GHz, 12 threads) Performance 35,6/64,9 Tflops 38 th position in Russian top 50 supercomputers rating RAM – 320 Gb Overall disk space volumes 86 Тb

11 HARDWARE & SOFTWARE ENVIRONMENT 11 VDI GPU 3D 1. GPU clusters ОC Gentoo & Open Grid Engine 2. VexCL (vector expression template library) OpenCL/CUDA 3. Simulation & analyze software system С++, MPI, Java 4. VDI server Citix XenDesktop & NVidia GRID 5. Data warehouse PostgreSQL & NFS (RAID)

12 WORKFLOW 12 Sensors data Simulation data Processing 3D full wave simulation GPU cluster Interpretation

13 SUCCESSFUL SOLUTIONS 13 Cloud solution Amazon SOFTWARE – HPC ENVIRONMENT OpenCL, CUDA, OpenMP, MPI HARDWARE – GPU CLUSTER Local solution T-platforms, Meijin, ARBYTE SC, STSS

14 PROBLEMS 14 DISTRIBUTED RENDERING REMOTE & SHARED ACCESS BIG DATA MANAGMENT INTEGRATION HPC2D&3DRDStore

15 INTEGRATED FRAMEWORKS 15 SCHLUMBERGER OCEAN HUE SPACE NVIDIA INDEX COMMERCIAL AND PROPRIETARY NVIDIA TECHNOLOGY C++,.NET, Java

16 SPECIALIZED FRAMEWORKS 16 Open Inventor, Nvidia Engines (SceniX, OptiX…), Equalizer, Chromium... HPC Hadoop, HPCC, Array-based DBMS (Rasdaman, SciDB)... NVidia CUDA Toolkit, AMD OpenCL SDK... Big Data Визуали зация

17 CONCLUSION 17 HPC HARWARE & SOFTWARE EXISTS INDUSTRIAL SPECIALIZATION COMPLETE DATA & PROCESSES INTEGRATION METHODOLOGY COMMON HPC SOFTWARE ECOSYSTEM SOFTWARE FRAMEWORKS HARD CHOICE

18 18 THANK YOU FOR YOUR ATTENTION!


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