• Lectures: M W 9:30-10:45 PHELP 1160
  Discussion Section: Thur 4:00- 4:50 PHELP 1445 or 5:00- 5:50 PHELP 1448

• Instructor: Tao Yang (tyang at cs).
  Office Hours: Mon/Wed after class -11:45

• TAs:
  Parker Carlson (Office Hours: Tues. 1:00-3:00 PM, HFH 5106)
  Shanxiu He (Office Hours: Mon/Thur 8:30-9:30 AM, HFH 5106)

• Parallel architecture, high performance computing, and performance evaluation
• Patterns of parallelism and program partitioning/mapping
• Distributed memory programming with message-passing interface (MPI)
• Shared memory programming with OpenMP and Pthreads
• Program parallelization of core algorithms in machine learning and scientific computing (matrix multiplication, equation solving, and model training)
• CUDA parallel programming with GPUs
• MapReduce and Spark programming for data intensive cloud computing

Prerequsites :

• Linear algebara (Math 4A).
• Programming experience with C on Linux.
• Knowledge of data structure and algorithms (mainly arrays and lists)
• Concepts: Algorithm complexity and partial derivatives

• Class schedule

• Class Policy

• References:
  
  • "An Introduction to Parallel Programming" by Peter Pacheco, 2011. Used in the past for this course. Author's website.
  • Introduction to High Performance Scientific Computing by David L. Chopp. SIAM 2019 Author's website
  • Additional online references are in weekly class schedule