Basic Information

  • Course description, goals, integrity, knowledge base
  • Course number: 263-2300, 6 credits
  • Spring 2017, lectures: M 10:15-12:00, HG D3.2; Th 9:15-10:00 CAB G51; occasional substitute lectures: W 13:15-15:00 HG D3.2
  • Instructor: Markus Püschel
  • TAs:
    • Alen Stojanov
    • Georg Ofenbeck
    • Gagandeep Singh
    • Only for project supervision: Daniele Spampinato

Grading

  • 40% research project
  • 25% midterm
  • 35% homework
  • There is no final Exam

Research Project

# Title Supervisor/s
1 Ant-inspired edge detection GO
2 t-Distributed stochastic neighbor embedding MP
3 Marching cubes GS
4 Locality sensitive hashing GS
5 PatchMatch algorithm GO
6 Fractal compression AS
7 Fast ray tracing for TSDFs GS
8 Binary convolutional neural network MP
9 A robust descriptor for line matching GO
10 Latent Dirichlet Allocation GO
11 Ray tracing GS
12 Medial axis transform GO
13 Quantized neural networks AS
14 Matrix multiplication over GF(2) AS
15 Non-linearly coupled elliptic BFPs GO
16 GP-UCB MP
17 Online dictionary learning for sparse coding MP

Midterm

26.4, 13:15 - 15:00, HG E5 (solution, without solution).

Homework

Homework Deadline Solution
Homework 0 as soon as possible  
Homework 1 Th March 9th, 5pm Solution
Homework 2 Th March 16th, 5pm Solution
Homework 3 Th March 30th, 5pm Solution
Homework 4 Th April 13th, 5pm Solution
Project milestone: update status in project system Fr May 5th, 5pm  

Lectures (including pdfs)

Date Content Notes Other
20.02 Course motivation, overview, organization    
23.02 Cost analysis and performance    
27.02 Intel Haswell architecture and microarchitecture, memory- and compute-bound   Intel Haswell, Intel Optimization Manual, Agner Fog’s instruction tables
01.02 Instruction-level parallelism and Compiler limitations    
06.03 Benchmarking, SIMD (SSE, AVX) overview    
13.03 SIMD (SSE, AVX) intrinsics   Intel Intrinsics Guide
16.03 SIMD (SSE, AVX)    
22.03 Locality, caches    
23.03 Caches, analysis of blocked MMM notes  
27.03 Roofline model notes paper
30.03 Linear algebra libraries, LAPACK, BLAS, ATLAS    
03.04 Fast MMM (model-based ATLAS) notes fast MMM paper
07.04 Fast MMM, register renaming    
10.04 Virtual memory system notes  
12.04 Memory bound computations, sparse MVM    
24.04 Sparse MVM, linear transforms    
26.06 Midterm exam    
04.05 Fast Fourier transform notes  
08.05 Optimizing FFT, FFTW notes fftw website
15.05 Spiral: program generation for transforms   spiral website
22.05 cancelled    
29.05 Project presentations    
31.05 Project presentations    
01.06 Project presentations