Toward Gear-Change and Beam-Beam Simula5ons with GHOST Bala Terzi - - PowerPoint PPT Presentation

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Toward Gear-Change and Beam-Beam Simula5ons with GHOST Bala Terzi - - PowerPoint PPT Presentation

Jan 31, 2023 232 likes •450 views

Toward Gear-Change and Beam-Beam Simula5ons with GHOST Bala Terzi Department of Physics, Old Dominion University Center for Accelerator Studies (CAS), Old Dominion University JLEIC CollaboraCon MeeCng, Jefferson Lab, March 31, 2016 1

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SLIDE 1

Toward Gear-Change and Beam-Beam Simula5ons with GHOST

Balša Terzić

Department of Physics, Old Dominion University

Center for Accelerator Studies (CAS), Old Dominion University

JLEIC CollaboraCon MeeCng, Jefferson Lab, March 31, 2016

March 31, 2016 Toward Gear-Change with GHOST

1

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SLIDE 2

Interdisciplinary Collabora5on

March 31, 2016 2

Jefferson Lab (CASA) Collaborators:

Vasiliy Morozov, He Zhang, Fanglei Lin, Yves Roblin, Todd Satogata

Old Dominion University (Center for Accelerator Science):

Professors:

Physics: Alexander Godunov Computer Science: Mohammad Zubair, Desh Ranjan Graduate students: Computer Science: Kamesh Arumugam, Ravi MajeC Physics: Chris Cotnoir, Mark Stefani

Toward Gear-Change with GHOST

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SLIDE 3

Outline

March 31, 2016 Toward Gear-Change with GHOST 3

  • MoCvaCon and Challenges
  • Importance of beam synchronizaCon
  • ComputaConal requirements and challenges
  • GHOST: New Beam-Beam Code
  • Outline
  • Present and future capabiliCes
  • Proposed implementaCon for beam synchronizaCon
  • Status and Timetable
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SLIDE 4

Mo5va5on: Implica5on of “Gear Changing”

March 31, 2016 Toward Gear-Change with GHOST 4

  • SynchronizaCon – highly desirable
  • Smaller magnet movement
  • Smaller RF adjustment
  • DetecCon and polarimetry – highly desirable
  • CancellaCon of systemaCc effects associated with bunch charge

and polarizaCon variaCon – great reducCon of systemaCc errors, someCmes more important than staCsCcs

  • Simplified electron polarimetry – only need average polarizaCon,

much easier than bunch-by-bunch measurement

  • Dynamics – quesCon
  • Possibility of an instability – needs to be studied

(Hirata & Keil 1990; Hao et al. 2014)

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SLIDE 5

Computa5onal Requirements

March 31, 2016 Toward Gear-Change with GHOST 5

  • PerspecCve: At the current layout of the MEIC

1 hour of machine operaCon Cme ≈ 400 million turns

  • Requirements for long-term beam-beam simulaCons of MEIC

① High-order symplecCc parCcle tracking ② Speed ③ Beam-beam collision ④ “Gear changing”

  • Our main charge is two-fold:
  • Do it right:
  • High-order symplecCc tracking
  • Do it fast:
  • One-turn maps, approximate beam-beam collisions
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SLIDE 6

GHOST: Outline

March 31, 2016 Toward Gear-Change with GHOST 6

  • GHOST: Gpu-accelerated High-Order SymplecCc Tracking
  • Our philosophy: Resolve computaConal bomlenecks by
  • Employing Bassen-Erskine approximaCon for collisions
  • ImplemenCng the code on a massively-parallel GPU plaoorm
  • GPU implementaCon yields best returns when:
  • The same instrucCon for mulCple data (parCcle tracking)
  • No communicaCon among threads (parCcle tracking)
  • Two main parts:

① ParCcle tracking ② Beam collisions

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SLIDE 7

GHOST: Symplec5c Par5cle Tracking

March 31, 2016 Toward Gear-Change with GHOST 7

  • SymplecCc tracking is essenCal for long-term simulaCons

Symple5c Tracking 500 000 iteraCons, 3rd order map

x Energy not conserved Par5cle will soon be lost Energy conserved

Non-Symple5c Tracking 500 000 iteraCons, 3rd order map

x px px

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SLIDE 8

GHOST: Symplec5c Par5cle Tracking

March 31, 2016 Toward Gear-Change with GHOST 8

  • Higher-order symplecCcity reveals more about dynamics

2nd order symplec5c 4th order symplec5c 3rd order symplec5c 5th order symplec5c 5000 turns

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SLIDE 9

GHOST: Symplec5c Par5cle Tracking

March 31, 2016 Toward Gear-Change with GHOST 9

  • SymplecCc tracking in GHOST is the same as in COSY Infinity

(Makino & Berz 1999)

  • Start with a one-turn map
  • SymplecCcity criterion enforced at each turn
  • Involves solving an implicit set of non-linear equaCons
  • Introduces a significant computaConal overhead

x = X

αβγηλµ

M(x|αβγηλµ)xαaβyγbηlλδµ

IniCal coordinates Final coordinates

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SLIDE 10

GHOST: Symplec5c Par5cle Tracking

March 31, 2016 Toward Gear-Change with GHOST 10

  • SymplecCc tracking in GHOST is the same as in COSY Infinity

(Makino & Berz 1999)

Non-Symple5c Tracking 3rd order map COSY GHOST 100,000 turns Symple5c Tracking 3rd order map COSY GHOST 100,000 turns

Perfect agreement!

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SLIDE 11

GHOST: Symplec5c Par5cle Tracking

March 31, 2016 Toward Gear-Change with GHOST 11

  • Dynamic aperture comparison to Elegant (Borland 2000)
  • 400 million turn simulaCon (truly long-term)

GHOST Elegant 1,000 turns Symple5c Tracking 4th order map

Excellent agreement!

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SLIDE 12

GHOST: Beam Collisions

March 31, 2016 Toward Gear-Change with GHOST 12

  • Bassen-Erskine ApproximaCon
  • Beams treated as 2D transverse Gaussian slices

(Good approximaCon for the JLEIC)

  • Poisson equaCon reduces to a complex error funcCon
  • Finite length of beams simulated by using mulCple slices
  • We generalized a “weak-strong” formalism of Bassen-Erskine
  • Include “strong-strong” collisions (each beam evolves)
  • Include various beam shapes (original only flat beams)
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SLIDE 13

GHOST Benchmarking: Collisions

March 31, 2016 Toward Gear-Change with GHOST 13

  • Code calibraCon and benchmarking
  • Convergence with increasing number of slices M
  • Comparison to BeamBeam3D (Qiang, Ryne & Furman 2002)

GHOST, 1 cm bunch 40k par5cles

Excellent agreement with BeamBeam3D

BeamBeam3D & GHOST, 10 cm bunch 40k par5cles

Finite bunch length accurately represented

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SLIDE 14

GHOST Benchmarking: Hourglass Effect

March 31, 2016 Toward Gear-Change with GHOST 14

  • When the bunch length σz ≈ β*at the IP, it experiences a

geometric reducCon in luminosity – the hourglass effect (Furman 1991)

GHOST, 128k par5cles, 10 slices

Excellent agreement with theory

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SLIDE 15

GHOST: GPU Implementa5on

March 31, 2016 Toward Gear-Change with GHOST 15

100k par5cles, varying # of GPUs

400 million turns in an JLEIC ring for a bunch with 100k par5cles: < 7 hr non-symplec5c, ~ 4.5 days for symplec5c tracking

1 GPU, varying # of par5cles

GHOST: 3rd order tracking

Speedup on 1 GPU over 1 CPU over 280 5mes With each new GPU architecture, performance improves

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SLIDE 16

GHOST: Beam Synchroniza5on

March 31, 2016 Toward Gear-Change with GHOST 16

  • Gear change requires many collisions per crossing (≈ 3400)
  • The load can be alleviated by implementaCon on GPUs
  • The informaCon for all bunches stored: huge memory load
  • Now more interesCng to CS folks: truly parallel problem
  • Prognosis:
  • Gear change is implementable, but will slow the code down
  • Long-term simulaCons may not be so “long”
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SLIDE 17

GHOST: Status

March 31, 2016 Toward Gear-Change with GHOST 17

  • Stage 1: ParCcle tracking (COMPLETED)
  • High-order, symplecCc tracking opCmized on GPUs
  • Benchmarked against COSY: Exact match
  • 400 million turn tracking-only simulaCon completed
  • Submimed for publicaCon (Phys. Rev. Accel. Beams)
  • Stage 2: Beam collisions (CURRENTLY UNDERWAY)
  • Bassen-Erskine collision implemented on GPUs
  • ValidaCon, benchmarking and opCmizaCon currently underway
  • Single bunch simulaCons in the summer
  • MulCple bunch simulaCons by the end of the year
  • Stage 3: Other effects to be implemented (YEAR 2 & BEYOND)
  • Other collision methods: fast mulCpole
  • Space charge, synchrotron radiaCon, IBS
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SLIDE 18

March 31, 2016 Toward Gear-Change with GHOST 18

Backup Slides

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SLIDE 19

GHOST GPU Implementa5on

March 31, 2016 Toward Gear-Change with GHOST 19

GHOST Tracking on 1 GPU

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SLIDE 20

JLEIC Design Parameters Used

March 31, 2016 Toward Gear-Change with GHOST 20