# Presentation: 335293

## High Energy Physics Greenbook Presentation

Robert D. Ryne
Lawrence Berkeley National Laboratory

NERSC User Group Meeting
June 25, 2005

**Robert D. Ryne**
**Lawrence Berkeley National Laboratory**
**NERSC User Group Meeting**
**June 25, 2005**

## Outline

- Lattice QCD
- Accelerator Physics
- Astrophysics (see D. Olson’s presentation)

## Lattice QCD

## Goals

- Determine a number of basic parameters of the Standard Model
- Make precise tests of the Standard Model
- Obtain a quantitative understanding of the physical phenomena controlled by the strong interactions

## Impact on determination of CKM matrix

- Improvements in lattice errors obtained w/ computers sustaining 0.6, 6, and 60 Tflops for one year

## Computing Needs: Approach

- Two pronged approach:
- Use of national supercomputer centers such as NERSC
- Build dedicated computers using special purpose hardware for QCD
- QCDOC
- Optimized clusters
- Special purpose hardware is used to perform the majority of the lattice calculations
- Supercomputer centers used for a combination of lattice calculations and data analysis

## Computational Issues

- Lattice calculations utilize a 4D grid
- Need highest possible single processor performance
- Communication is nearest-neighbor
- Don’t need large memory
- Do need high speed networks
- International Lattice Data Grid formed to share computationally expensive data
- Need to move ~1 petabyte in 24 hrs

## Lattice QCD Computational Roadmap

- Lattice community presently sustains **0.5-1 Tflop/sec**
- Has allowed determination of a limited number of key quantities to ~few percent accuracy
- Has allowed development & testing of new formulations of that will significantly improve accuracy of future calculations
- In next few years need to sustain **50-100 Tflop/sec**
- Calculate weak decay constants & form factors
- Determine phase diagram of high temp QCD, calculate EOS of quark-gluon plasma
- Obtain quantitative understanding of internal structure of strongly interacting particles
- Need to sustain ~ **1 petaflop/sec** by end of decade

## Accelerator Physics

## Goals

- Large-scale modeling is essential for
- Improving/upgrading existing accelerators
- Designing next-generation accelerators
- Exploring/discovering new methods of acceleration
- Laser/plasma based concepts

## Accelerator modeling is very diverse

- Many models
- Maxwell
- Vlasov/Poisson
- Vlasov/Maxwell
- Fokker-Planck
- Leonard-Weichart
- Single & multi-species
- Particle based codes
- Mesh-based codes: regular, irregular, AMR,...
- Combined particle/mesh codes
- Runs of various sizes (up to ~1000 PEs and beyond)

## Advanced Computing: An imperative to help assure success and best performance of a ~$20B investment

- SciDAC budget is < 0.02% of the this amount
- Small investiment in computing can have huge financial consequences

## Accelerator Modeling Roadmap

- Current resources: ~3M hrs/yr @ NERSC
- In the next few years, will need ~20M hrs/yr
- Design of proposed machines: Linear Collider, RIA, hadron machines (proton drivers, muon/neutrino systems, VLHC)
- Simulation of existing & near-term machines: LHC,RHIC, PEP-II, SNS
- Design of advanced concepts: 1 GeV stage, plasma afterburner
- Design of 4th generation light sources
- By the end of the decade will need ~60M hrs/yr
- Full scale _electron-cloud_
- Multi-slice, multi-IP, _strong-strong beam-beam_
- Interaction of space charge effects, wakefields, and machine nonlinearities in _boosters and accumulator rings_
- First principles Langevin modeling of _electron cooling_ systems
- _CSR_ effects with realistic boundary conditions
- Goal is end-to-end modeling of complete systems

## Algorithmic & Software Needs

- Continued close collaboration with ASCR-supported researchers is **essential**
- Linear solvers, eigensolvers, PDE solvers, meshing technologies, visualization
- Performance monitoring and enhancement, version control & build tools, multi-language support
- Multi-scale methods are becoming increasingly important
- We need robust, easy-to-use parallel programming environments & parallel scientific software libraries

## Parallel Optimization promises to be well suited for design problems on 10’s of thousands of processors

- Machine design always involves multiple runs
- Up to now the community has learned how to run large problems on ~thousand processors
- In the future, it will be desirable to run multiple ~1000 processor runs in a single optimization step
- Will allow scaling up to 10’s of thousands of processors for machine design problems
- NOTE: not all problems are design problems. Fast interprocessor communication is needed for the very largest “single point” runs.

## Diversity of accelerator modeling problems demands a mix of capacity & capability, and a mix of system parameters

- Some problems well suited to <=500 processors, but we typically need to run a large # of simulations
- Design studies, parameter scans
- Some problems demand large simulations (>=1000) procs) and involve regular, near-neighbor comm.
- Electromagnetic PIC
- Some problems demand large simulations and involve global, irregular communication
- Modeling geometrically complex electromagnetic structures

## THE END