COMPENG%20701

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COMPENG 701

• FOUNDATIONS OF MODERN SCIENTIFIC PROGRAMMING

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Course Information

• Instructor Yuriy Zinchenko,
• Information Technology Building 221,
  zinchen_at_mcmaster.ca,
• course syllabus at
• http//optlab.mcmaster.ca/yzinchen/
• Time and location
• Thursday, 1030-1330,
• ITB 235

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Course Goals

• introduce to high-performance/high-throughput
  computing
• equip with basic knowledge of computing tools
  available
• The course is self-contained, tutorial-based.
• Focus Basic Linear Algebra Subprograms

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Tentative Layout

• introductory lecture
• file systems, binary systems, computer and
  processor architecture
• Linux/Unix and Windows operating systems
• introduction to MATLAB and Octave
• introduction to C and Fortran
• BLAS
• memory management and processor architecture for
  high-performance computing, compiler flags,
  tuning BLAS, Automatically Tuned Linear Algebra
  Software
• writing fast code in MATLAB
• external libraries with MATLAB/Octave, MEX files,
  BLAS interfacing
• introduction to parallel computing, cluster and
  multi-processor system (MPS) environments
• C/Fortran for high-performance computing on MPS,
  OpenMP,
• using clusters (SHARCNET)

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Typical Applications for BLAS

• numerical PDEs
• image processing
• core of most optimization engines
• many others
• Important always exploit data structure!

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An Example

• Radiation Therapy for Cancer Treatment
• Background
• About 1.3 million new cancer cases in the U.S.
  each year
• Nearly 60 receive radiation therapy, in
  conjunction with surgery, chemotherapy, etc.

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External beam radiation therapy

• Radiation delivered by a linear accelerator
• Cancer cells more susceptible than normal cells
• Dose given in daily fractions for 6 weeks
• Overlay beams from different angles

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Intensity Modulated Radiation Therapy

• Block parts of the radiation beam discretize
  the beam into smaller beamlets
• Choose different intensities for each beamlet

Intensity Modulated Radiation Therapy
Collaborative Working Group, 2001
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Treatment planning
Goal Choose beam angles and beamlet
intensities that kill tumor and spare healthy
tissues

• Take CT scan
• Delineate
• Discretize body into voxels
• Formulate solve a mathematical program to find
  a good plan

Princess Margaret Hospital
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One facet of RT treatment planning

• Formulate and solve inverse problem to find
  beamlet intensities that satisfy clinical
  objectives
• Assuming all the input data are error-free
• Common approach use optimization

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Calculating dose delivered

• Dose delivered to voxel
• w(b) intensity of
• beamlet b
• (decision variable)
• Dose(b,v) dose
• to voxel v
• from beamlet b
• (parameter)

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Types of models

• Common objectives
• Maximize the minimum dose to the target region
• Minimize deviations from prescribed dose
• Common constraints
• Homogeneity
• Maximum dose constraints
• Dose-volume constraints

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How to deliver ?

• Bad news sensitive to errors

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Uncertainties

• Setup errors
• Patient motion
• Structural changes during treatment
• uncertainty in geometry
• A direction rescan to eliminate some of these
  errors

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What can go wrong?

• A simple LP problem
• max x y
• s.t. x.99 y ? 1 x, y ? 0

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A new problem

• Given image A and its perturbed copy B, how can
  we match those?

?
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Assignment 1

• MATLAB code and data are posted on the web. The
  image recovery is performed via naïve local
  search amongst the sequence of translations and
  rotations (e.g., lines 21-30 of the code).
• 0. Fill in the survey form on the next page.
• Would anything change if we replace line 26 with
  line 27? Which one would you prefer? Explain both
  parts.
• The translation/rotation transformation is
  implemented as series of operations on the
  intensity matrix (e.g., scan2). Write this
  operation in matrix-vector form, i.e., as ABCD
  for some matrices A,B,C and D.
• Are any of the data structures in 2 sparse, that
  is, have big blocks of zeros? Can one potentially
  take advantage of this?
• Bonus question implement the sparse
  matrix-vector multiplication routine in MATLAB
  (may use C but no external libraries). The
  fastest code gets bonus points.

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Background survey

• Name Degree you pursuing (MS/PhD) Department
  
• 1. Rank your answer from 1-no idea to 5-expert
  level to the following questions how familiar
  are you with

Linux/Unix OS
Windows OS
MATLAB
Octave
BLAS
ATLAS
C
Fortran
OpenMP
MPI
2. Circle one was todays class too
elementary just right too
complicated? 3. Reason for taking the course
required interest in the subject. 4. What
is the most important thing you would like to
learn in this class?