1. Lawrence Berkeley National Laboratory Kathy Yelick Associate Laboratory Director for Computing Sciences

2. Berkeley Lab Changes Science 13 Nobel Prizes 4200 employees $820M funding Operated by UC 1000 student 250 faculty

3. The Joint Genome Institute 1,000 Users NERSC 5,608 Users 2,443 Users Berkeley Lab User Facilities Enable SC Community to Discover, Learn, and Create The Advanced Light Source 616 Users The Molecular Foundry & NCEM All numbers from FY2014 Energy Sciences Network 240 Petabytes/yr.

4. Scientific Areas at Berkeley Lab Energy Sciences Biology and the Environment Computing Physical Sciences Operations

5. Computing Sciences Area at Berkeley Lab Computing Sciences Area Computational Research Applied Math Computer Science Data Science Computational Science Esnet Facility NERSC Facility ~$150M Funding Included Science Engagement and Support

6. Computing Sciences Vision Achieve transformational, breakthrough impacts in scientific domains through the discovery and use of advanced computational methods and systems and make them accessible to the broad science community.

7. Disruptions in Computing Over 10 Years Redefine Best-in-Class Facilities Computing performance growth stalls twice New science problems require new mathematics EXASCAL E MATH Experiment and observation will require advanced computing DATA Engaged in New Science Domains and Questions

8. Exascale Goals: Broad Science Impact Co-Design systems for simulation and analysis Portable and productive exascale software stack Suite of AMR applications including climate and combustion NERSC deploys the first exascale system capability of running diverse simulation and data worloads in 2024 Materials and chemistry applications using sparse and real- space methods Applications achieve 500x current NERSC capability by 2025

9. Data Growth is Outpacing Computing Growth Graph based on average growth

10. High end computing has focused on simulation ExperimentationTheory Simulation Data Analysis 10 Computing

11. Data analysis is equally important in Science Experimentation Theory SimulationData Analysis Computing Growth in Sequencers, CCDs, sensors, etc. 11

12. “Superfacility” for Experimental Science Data Systems, Services and Research MS- DESI ALSLHCJGI APSLCLS Other data- producing sources

13. Data collection with robots and high resolution detectors (GISAX) Transfer to NERSC FFT + mask data from experiment Analysis and modeling at NERSC, ORNL, or ANL HipGISAXS simulation HipRMC fitting FFT Compare start with random system move particle random Autotuning On-the-fly calibration, processing SPOT Suite: Real-time access via web portal Light Source: Envisioning a “Super Facility”

14. Interdisciplinary Data Science at Berkeley Lab PTF Super- nova Planck CMB Alice LHC Atlas LHC MP MGI Carbon Flux* Sensors Daya Bay Neu- trinos ALS Light source LCLS Light source Bio- Imaging Rad- Map Sensors JGI Bio Open- MSI mass spec KBase Bio HEP, NERSCNASA, HEPNPHEP BES,EERE, NERSC EEREHEP LDRD, ALS, NERSC, ESnet, ASCR LDRDDHSJGI, LDRD“LDRD” BER, NERSC

15. CRT: A Facility for Discoveries with Computing - 15 - CRT Substantia l Completio n 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 NERSC -8 Cori Phase II NERSC -8 Cori Phase I CRT 20 MW upgrad e NERSC -9 150- 300 Petaflo p CRT 40 MW upgrad e NERSC-10 Capable Exascale for broad Science ESnet-6 Deploye d ESnet-6 upgrade begins ESnet testbed upgrade Staff move in NRP complete 12.5 MW

16. Computational Research and Theory (CRT): A Building Designed for Exascale Systems Substantial occupancy in Spring 2015: 4-story, 76,000 sq ft facility  270 offices in collaborative office setting (2 x 20,000 sq ft floors)  $143M UC Building, $19.9M DOE computing infrastructure  21,000 sq ft HPC floor  Come to tribbon cutting on November 12th Energy efficient  Year-round air cooling  PUE < 1.1  LEED Gold design 42MW to building  12.5MW provisioned  Low cost WAPA power  Additional power needed for future systems In 2016, NERSC-8 (“Cori”) will move SC users toward exascale, offering 10x NERSC-6 on key applications and 15x more energy efficiency

17. Goal: To enable new modes of scientific discovery Scientific Discovery Growth in Data New Analysis Methods New Science Processes - 17 - Detectors Robotics Sensors Image Analysis Machine Learning Combine observation and simulation Re-use and Re-analyze