Difference between revisions of "CoE 163 S2 AY 2021-2022"

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m (Updated grading rubric)
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* Darvy P. Ong [darvy.ong at eeemail]
 
* Darvy P. Ong [darvy.ong at eeemail]
 
* Nestor Michael C. Tiglao [nestor at eeemail]
 
* Nestor Michael C. Tiglao [nestor at eeemail]
 +
'''Student Assistants''':
 +
* Brian Bascos
 +
* Christian Eric Cosca
 +
* Jean Abigail de Padua
 
'''Synopsis''': This course aims to 1) present the connection between algorithms, implementation, and computer architecture, 2) provide tools needed to write and apply fast numerical code, and 3) present representative fundamental numerical algorithms.
 
'''Synopsis''': This course aims to 1) present the connection between algorithms, implementation, and computer architecture, 2) provide tools needed to write and apply fast numerical code, and 3) present representative fundamental numerical algorithms.
 
<br>
 
<br>
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[[:File:Coe163 2020s2 Syllabus.pdf | [guide]]]<br>
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[[:File:Coe163 2s2122 syllabus.pdf | [guide]]]<br>
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[[:File:Coe163 2020s2 00 about.pdf | [00 slides]]]
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[[:File:Coe163 2s2122 00 about.pdf | [00 slides]]]
 
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* [01b] Problem identification and solving
 
* [01b] Problem identification and solving
 
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[SQW01] CS problems<br>
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[SQ01] CS problems<br>
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[<nowiki>[SQW01] Submission bin</nowiki>]<br>
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[https://uvle.upd.edu.ph/mod/quiz/view.php?id=156604 <nowiki>[SQ01] Quiz</nowiki>]<br>
 
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[[:File:Coe163 2020s2 01a review algorithms.pdf | [01a slides]]]<br>
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[[:File:Coe163 2s2122 01a review algorithms.pdf | [01a slides]]]<br>
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[[:File:Coe163 2020s2 01b problem solving.pdf | [01b slides]]]
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[[:File:Coe163 2s2122 01b problem solving.pdf | [01b slides]]]
 
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| 2
 
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* [02a] Review of asymptotic analysis
 
* [02a] Review of asymptotic analysis
 
* [02b] Amortized analysis
 
* [02b] Amortized analysis
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* [02c] High-level code translation to memory
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* [02c] High-level optimization
 
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[SEW02] Asymptotic analysis<br>
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[SQ02] Asymptotic analysis<br>
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[<nowiki>[SEW02] Submission bin</nowiki>]<br>
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[https://uvle.upd.edu.ph/mod/quiz/view.php?id=156608 <nowiki>[SQ02] Quiz</nowiki>]<br>
 
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[[:File:Coe163 2020s2 02a review asymptotic.pdf | [02a slides]]]<br>
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[[:File:Coe163 2s2122 02a review asymptotic.pdf | [02a slides]]]<br>
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[[:File:Coe163 2020s2 02b amortized analysis.pdf | [02b slides]]]<br>
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[[:File:Coe163 2s2122 02b amortized analysis.pdf | [02b slides]]]<br>
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[02c slides]
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[[:File:Coe163 2s2122 02c high level optimization.pdf | [02c slides]]]
 
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| 3
 
| 3
 
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* [03a] Programming languages survey
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* [03a] Choosing a platform
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* [03b] Matching programming languages and problems
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* [03b] x86 assembly introduction
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* [03c] Introduction to x86 assembly
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* [03c] x86 assembly reference
 
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[SEW03] Solving and profiling<br>
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[SE01] Profiling and assembly<br>
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[[SEW03] Specifications]]<br>
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[[:File:Coe163 2s2122 se01 profiling assembly.pdf | [SE01] Specifications]]<br>
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[<nowiki>[ME01] Submission bin</nowiki>]
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[https://uvle.upd.edu.ph/mod/assign/view.php?id=195394 <nowiki>[SE01] Submission bin</nowiki>]
 
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[[:File:Coe163 2020s2 03a high level optimization.pdf | [03a slides]]]<br>
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[[ | [03a slides]]]<br>
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[[:File:Coe163 2020s2 03b parallel programming intro.pdf | [03b slides]]]<br>
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[[:File:Coe163 2s2122 03b x86 assembly.pdf | [03b slides]]]<br>
 +
[[:File:Coe163 2s2122 03c x86 assembly ref.pdf | [03c slides]]]
 
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| 4
 
| 4
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* [04c] Cache behavior of linear algebra operations
 
* [04c] Cache behavior of linear algebra operations
 
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|
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[SQW04] Linear algebra<br>
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[SQ03] Linear algebra<br>
 
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[[:File:Coe163 2020s2 04a linear algeb ops.pdf | [04a slides]]]<br>
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[[ | [04a slides]]]<br>
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[[:File:Coe163 2020s2 04b linear algeb problems.pdf | [04b slides]]]<br>
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[[ | [04b slides]]]<br>
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[[:File:Coe163 2020s2 04c linear algeb considerations.pdf | [04c slides]]]<br>
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[[ | [04c slides]]]<br>
 
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* [05c] ATLAS (automatically-tuned linear algebra software)
 
* [05c] ATLAS (automatically-tuned linear algebra software)
 
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[SEW05] Caching in MMM<br>
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[SE02] Caching in MMM<br>
 
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[[:File:Coe163 2020s2 05a cache.pdf | [05a slides]]]<br>
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[[ | [05a slides]]]<br>
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[[:File:Coe163 2020s2 05b mmm part01.pdf | [05b slides]]]<br>
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[[ | [05b slides]]]<br>
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[[:File:Coe163 2020s2 05c mmm part02.pdf | [05c slides]]]<br>
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[[ | [05c slides]]]<br>
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[[:File:Coe163 2020s2 05x study guide.pdf | [05x guide]]]<br>
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[[ | [05x guide]]]<br>
 
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| 6
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* [06b] Matrix inversion
 
* [06b] Matrix inversion
 
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[SEW06] BLAS<br>
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[SE03] BLAS<br>
 
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−
[[:File:Coe163 2020s2 06a blas atlas.pdf | [06a slides]]]
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[[ | [06a slides]]]
 
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| 7
 
| 7
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* [07b] Matrix decomposition
 
* [07b] Matrix decomposition
 
|
 
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−
[SQW07] Matrix Factorization and Sparse Matrices<br>
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[SQ04] Matrix Factorization and Sparse Matrices<br>
 
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[[:File:Coe163 2020s2 07a gaussian elim.pdf | [07a slides]]]<br>
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[[ | [07a slides]]]<br>
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[[:File:Coe163 2020s2 07b sparse mat.pdf | [07b slides]]]
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[[ | [07b slides]]]
 
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| 8
 
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* [10b] Limits of parallel computing
 
* [10b] Limits of parallel computing
 
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[SQW10] Parallel programming
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[SQ05] Parallel programming
 
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* [11a] Parallel computing algorithms
 
* [11a] Parallel computing algorithms
 
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[SEW11] Parallel computing algorithms
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[SE04] Parallel computing algorithms
 
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* [12b] OpenCL/OpenMP
 
* [12b] OpenCL/OpenMP
 
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[SEW12] OpenCL/OpenMP
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[SE05] OpenCL/OpenMP
 
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Revision as of 17:05, 3 March 2022

Course Information

Academic Period: 2nd Semester AY 2021-2022
Units: 3
Workload:

  • 3 hours lecture per week
  • 1-2 hours exercise per week

Instructors:

  • Isabel M. Austria [isabel.austria at eeemail]
  • Carl C. Dizon [carl.dizon at eeemail]
  • Darvy P. Ong [darvy.ong at eeemail]
  • Nestor Michael C. Tiglao [nestor at eeemail]

Student Assistants:

  • Brian Bascos
  • Christian Eric Cosca
  • Jean Abigail de Padua

Synopsis: This course aims to 1) present the connection between algorithms, implementation, and computer architecture, 2) provide tools needed to write and apply fast numerical code, and 3) present representative fundamental numerical algorithms.
Delivery Method: Video lectures and digital materials
Online Platforms: UVLe, Piazza, Google Meet, Zoom, other quiz platforms.

Course Outline

Week Topics Academic Requirements Resource Links
0
  • [00] Course overview and synopsis
  • [00] Course requirements

[guide]
[00 slides]

1
  • [01a] Review of CS data structures and algorithms
  • [01b] Problem identification and solving

[SQ01] CS problems
[SQ01] Quiz

[01a slides]
[01b slides]

2
  • [02a] Review of asymptotic analysis
  • [02b] Amortized analysis
  • [02c] High-level optimization

[SQ02] Asymptotic analysis
[SQ02] Quiz

[02a slides]
[02b slides]
[02c slides]

3
  • [03a] Choosing a platform
  • [03b] x86 assembly introduction
  • [03c] x86 assembly reference

[SE01] Profiling and assembly
[SE01] Specifications
[SE01] Submission bin

[[ | [03a slides]]]
[03b slides]
[03c slides]

4
  • [04a] Review of linear algebra operations
  • [04b] Solving problems using linear algebra
  • [04c] Cache behavior of linear algebra operations

[SQ03] Linear algebra

[[ | [04a slides]]]
[[ | [04b slides]]]
[[ | [04c slides]]]

5
  • [05a] Matrix-matrix multiplication part 01
  • [05b] Matrix-matrix multiplication part 02
  • [05c] ATLAS (automatically-tuned linear algebra software)

[SE02] Caching in MMM

[[ | [05a slides]]]
[[ | [05b slides]]]
[[ | [05c slides]]]
[[ | [05x guide]]]

6
  • [06a] Gaussian elimination
  • [06b] Matrix inversion

[SE03] BLAS

[[ | [06a slides]]]

7
  • [07a] Sparse linear algebra
  • [07b] Matrix decomposition

[SQ04] Matrix Factorization and Sparse Matrices

[[ | [07a slides]]]
[[ | [07b slides]]]

8
READING BREAK
9
LENTEN BREAK
10
  • [10a] Parallel computing concepts
  • [10b] Limits of parallel computing

[SQ05] Parallel programming

11
  • [11a] Parallel computing algorithms

[SE04] Parallel computing algorithms

12
  • [12a] Single instruction multiple data vectorization
  • [12b] OpenCL/OpenMP

[SE05] OpenCL/OpenMP

13
  • [13a] GPU programming basics
  • [13b] CUDA programming with Numba

[CE] Capstone exercise

14
READING BREAK
15
16
17
  • Finals week

Grading Rubric

32% Short quizzes
48% Software exercises
20% Capstone exercise

Announcements

February 2022

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