The demand for computational speed

• Floating-Point Operation per Second (FLOPS)
  • Count number of floating-point calculations (arithmetic operations) per second.
• Not MIPS (millions of instructions per second) as MIPS also count non-arithmetic operations such as data movement or condition.

$FLOPS = sockets \times \frac{cores}{socket} \times \frac{cycles}{second} \times \frac{FLOPS}{cycle}$

• MFLOPS (megaFLOPS) = 1,000,000 FLOPS
• GFLOPS (gigaFLOPS) = 1,000,000,000 FLOPS

• TFLOPS (teraFLOPS) = 1,000,000,000,000 FLOPS
  • Intel’s ASCI Red for Sandia National Laboratory (DOE) was the first supercomputer in the world to achieve 1 TFLOPS in 1997.
  • ASCI Red is used for large-scale simulation in nuclear weapon development and material analysis.
• PFLOPS (petaFLOPS) = 1,000,000,000,000,000 FLOPS
  • IBM RoadRunner for Los Alamos National Laboratory (DOE) was the first supercomputer to achieve 1 PFLOPS in 2008.
  • Oak Ridge National Laboratory’s Summit (DOE) is the second fastest supercomputer in the world at 148.6 PFLOPS.
  • Fugaku of RIKEN Center for Computational Science (Japan) is the current fastest supercomputer at 415 PFLOPS.
• EFLOPS (exaFLOPS) = 1,000,000,000,000,000,000 FLOPS
  • November 2024
    • Aurora: 1.9 EFLOPS, Argonne National Lab, Intel
    • Frontier: 2.0 EFLOPS, Oak Ridge National Lab, AMD
    • El Capitan: 2.7 EFLOPS, Lawrence Livermore National Lab, AMD
  • Tianhe 3 (first China Exascale computer, 2020, National University of Defense Technology)
    • China no longer participates in the TOP500 list reporting
  • Subsequent update to Fugaku (first Japan Exascale computer, 2026, RIKEN Center for Computational Science)
  • Europe’s Jupiter, hosted at Julich Supercomputing Center, Germany, will be the first Exascale supercomputer for Europe.

• List the 500 most powerful computers in the world.
• Count FLOPS by having supercomputer runs well-known computationally intensive tasks
  • Solve $Ax=b$, dense random matrix problem.
  • Primarily dense matrix-matrix multiplications.
• Updated twice a year:
  • International Supercomputing conference (June, Germany)
  • Supercomputing conference (November, US).
• Website: http://www.top500.org

• The four modern paradigms of science
  • Theory
  • Experiment
  • Simulation
  • Data analysis
• Simulation: study things that are too big, too small, too fast, too slow, too expensive, or too dangerous.
• Data analysis: study data that are too big, too complex, too fast (streaming data), too noisy.

• the deadliest and most destructive, as well as the strongest hurricane of the 2012 Atlantic hurricane season,
• the second-costliest hurricane on record in the United States (nearly $70 billion in damage in 2012),
• affected 24 states, with particularly severe damage in New Jersey and New York,
• hit New York City on October 29, flooding streets, tunnels and subway lines and cutting power in and around the city.

• Geophysical Fluid Dynamic Laboratory hurricane model (National Oceanic and Atmospheric Administration)
• Hurricane Weather Research and Forecasting model (NOAA/Naval Research Laboratory/Florida State University)
• European Centre for Medium Range Weather Forecast model (ECMWF)
• Global Forecast Model (National Weather Service)
• Which model is closest to reality?

• http://blogs.agu.org/wildwildscience/2013/02/17/seriously-behind-the-numerical-weather-prediction-gap/

• NOAA Weather Computer upgrade
• Two new supercomputers, Luna and Surge
• 2.89 PFLOPS each for a total of 5.78 PFLOPS (previous generation is only 776 TFLOPS)
• Increase water quantity forecast from 4000 locations to 2.7 million locations (700-fold increase in spatial density)
• Can track and forecast 8 storms at any given time
• 44.5 million dollars investment

• US HPC Consortium to contribute to Covid research
  • Toward explaining signs of COVID symptoms
• Many other work (published in Nature) include supercomputing usages for molecular dynamic simulation/data analysis.

• For 767 development, Boeing built and tested 77 physical prototypes for wing design.
• For 787 development, only 11 prototypes were built.
  • Optimized via more than 800,000 hours of computer simulation.

• Los Alamos National Lab
• Development of large-scale data analytic techniques to simulate and predict subsurface fluid distribution, temperature, and pressure
• This reduces the need for observation wells (has demonstrated commercial success)

• 10M+ logins, 13M+ transactions, 300 variables per events
• ~4B inserts, ~8B selects
• MPI-like applications, Lustre Parallel File Systems, Hadoop Saved over $700M in fraudulent transactions during first year of deployment