Location: DH 1117 Overview: Zoom instead of HH A312: https://cmu.zoom.us/j/3201808397 email: franzf@ece.cmu.edu web: http://www.ece.cmu.edu/~franzf TA Sanil Rao office hours: Mondays 1:00pm–2:00pm. Zoom instead of HH 1305 email: sanilr@andrew.cmu.edu ECE IT Helpdesk: HH A204 walkin Monday–Friday 8:00am–5:00pm email: help@ece.cmu.edu Course Canvas link: https://canvas.cmu.edu/courses/13266 Tentative Course Calendar 
Date  Day  Class Activity 
January  
14  Tues.  State of computing: What is the current state of the art from embedded devices through desktops, servers, and consumer systems all the way to cloud, HPC, and supercomputing 
16  Thurs.  The ECE Computing Environment: number cluster, Andrew systems, capability machines, GPU access, cloud access, Pittsburgh Supercomputing Center and XSEDE 
21  Tues.  Computer architecture: Relevant computer architecture concepts 
23  Thurs.  Software stack: ISA, operating system, virtualization, messaging, containers 
28  Tues.  Mathematics for Engineers: The central role of numerical linear algebra 
30  Thurs.  Algorithm analysis, scalability, complexity: Getting answers in time 
February  
4  Tues.  Field trip: ECE Computing/Cyert Hall 
6  Thurs.  Parallelization: Sequential vs. parallel algorithms, scalability vs. performance 
11  Tues.  Need for speed: Principles of code optimization, when and how to optimize code 
13  Thurs.  Cloud computing and HPC: Amazon EC2/Windows Azure/Google Cloud, Computational Grids, Scientific Workflows, Computing Centers 
18  Tues.  Numerical Analysis: How good are your answers? How to make them better? 
20  Thurs.  Guest Lecture: Quantum Computing and Quantum Algorithms 
25  Tues.  Scalable algorithms: Dense numerical linear algebra, CNNs/DNNs/ FFTs 
27  Thurs.  Scalable algorithms: Graph algorithms and sparse numerical linear algebra 
March  
3  Tues.  Scalable algorithms: ODE and PDE solvers, stencils, filters, discretization 
5  Thurs.  Scalable algorithms: Discrete and continuous optimization, ML training 
6  Fri.  MidSemester Break; No Classes 
913  Spring Break; No Classes  
17  Tues.  Cancelled. Switching to Zoom online lectures. From now on: https://cmu.zoom.us/j/3201808397 
19  Thurs.  Scalable algorithms: Informatics, symbolic computing, higher level AI algorithms 
24  Tues.  Scalable algorithms: Statistics: Monte Carlo, MCMC, statistical machine learning 
26  Thurs.  Data and Visualization: Data sets, data visualization and tables, data bases 
31  Tues.  Modern CPUs: SuperScalar Outoforder, multicore, ISA extensions 
April  
2  Thurs.  Modern CPUs—Vector Extensions: How to double/quadruple your peak performance quickly 
7  Tues.  Hardware Acceleration: GPUs, FPGAs, TPU, Tensor Cores, . . . 
9  Thurs.  From productivity to performance: C++, OpenMP, MPI, CUDA, Autotuning 
14  Tues.  Homework—Lessons learned: What we learned and found strange 
1617  No Classes; Spring Carnival  
21  Tues.  Research Talk: SPIRAL: Formal Software Synthesis of Computational Kernels 
23  Thurs.  PhD Student Project Presentations 
28  Thurs.  Guest Lecture: Pittsburgh Supercomputing Center and Usable HPC and High Performance AI/ML 
30  Tues.  Summary: What we have learned and where to go from here 
MS Homework and PhD Project
Machines
In this course we will use a large variety of machines in the homeworks and projects:
Course Summary
Date  Details  Activity  Time 
Thu Feb 20, 2020  Assignment  MS: Homework 1: Getting Started, Scalability of Linear Algebra  due by 11:59pm 
Tue Mar 3, 2020  Assignment  MS: Homework 2: Parallelism, Scaling, Performance  due by 11:59pm 
Tue Mar 24, 2020  Assignment  MS: Homework 3: CNNs, DNNs and Graph Algorithms  due by 11:59pm 
Tue Apr 7, 2020  Assignment  MS: Homework 4: AI, ML, Statistics  due by 11:59pm 
Wed Apr 22, 2020  Assignment  PhD: Final Presentation  due by 11:59pm 
Tue Apr 28, 2020  Assignment  MS: Homework 5: Final Project: Blog Post  due by 11:59pm 
Thu Apr 30, 2020  Assignment  PhD: Final Project  due by 11:59pm 
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