Although accounts on the parallel server for the hands-on activity are
only available to on-site attendees, online attendees are welcome to do the homework on their own platforms.
Wednesday, August 15
*9:00 - 9:30- Introduction and Welcome (Jim Demmel, UCB) Slides and Video
Greeting, Overview, and talk about logistics
*9:30 - 12:00- Introduction to Parallel Architectures and Pthreads (John Kubiatowicz, UCB)Slides and Video
Why parallelism is our future, and what programmers need to know about the hardware in order to write efficient programs. We also introduce parallel programming with Pthreads. (includes 30 min break)
*12:00 - 1:15- Lunch
*1:15 - 2:15- Shared Memory Programming with OpenMP- Basics (Tim Mattson, Intel) Slides
We introduce OpenMP; an industry standard API for programming shared memory computers. OpenMP provides a simple path for programmers to get started with parallel programming. In this lecture, we'll focus on the core features of the original versions of OpenMP.
*2:15 - 3:00- More about OpenMP- New Features (Tim Mattson, Intel)Slides and Video
Since its introduction in 1997, OpenMP has grown beyond simple parallel loops. In this lecture we'll explore the more recent features with an emphasis on the tasking model added in OpeMP 3.0 and the classes of algorithms this model supports.
*3:00 - 3:30- Break
*3:30 - 4:30- Parallel Programming on Windows and Porting CS267
(Matej Ciesko, Microsoft) Slides and Video
*4:30 - 5:00- Break/ Transition to Rooms
*5:00 - 6:00- Hands-on Activity (Parallel Sessions):
Introduction to Microsoft Tools (Room 380)
Introduction to NERSC Tools (Rooms 273, 275, & 277)
*6:00 - 7:00- Informal Meet & Greet Reception (Soda Hall, 5th Floor)
Thursday, August 16
*8:45 - 9:45- Programming Distributed Memory Systems with MPI (Tim Mattson, Intel) Slides and Video
*9:45 - 10:45- Sources of Parallelism and Locality in Simulation (Jim Demmel, UCB) Slides and Video
We show how to recognize recurring opportunities to exploit parallelism in simulating real or artificial "worlds", as well as opportunities to minimize data movement.
*10:45 - 11:15- Break
*11:15 - 12:15- Architecting Parallel Software with Patterns (Kurt Keutzer, UCB)Slides
We give an overview of design patterns and how complex parallel software systems can be architected with them.
*12:15 - 1:30- Lunch
*1:30 - 2:30- An Introduction to GPU, CUDA, and OpenCL (Bryan Catanzaro, NVIDIA Research) Slides and Video
GPUs (Graphics Processing Units) have evolved into programmable manycore parallel processors. We will discuss the CUDA and OpenCL programming models, GPU architecture, and how to write high performance code on GPUs.
*2:30 - 3:00- Break/ Transition to Room 380 for Microsoft Tools, and Rooms 273, 275, & 277 for NERSC Tools, all rooms located in Soda Hall
*3:00 - 6:00- Hands-on Activity
Friday, August 17
*8:45 - 9:45-Partitioned Global Address Space Programming with Unified Parallel C (UPC) (Kathy Yelick, UCB)Slides and Video
The largest and highest performance computers have distributed memory instead of shared memory, and are programmed using message passing (MPI)or new languages like UPC.
*9:45 - 10:15- Break
*10:15 - 12:15- Computational Patterns and Autotuning (Jim Demmel, UCB)Slides and Video
We discuss several recurring computational patterns (eg linear algebra and stencils) whose fastest implementations are written automatically by other programs called autotuners.
*12:15 - 1:30- Lunch
*1:30 - 2:30- Performance Debugging: Methods and Tools (David Skinner, LBL)Slides and Video
When a parallel program runs slower than expected, "performance debugging" may be done most effectively using a variety of tools that automatically instrument and display performance data.
*2:30 - 3:30- Cloud Computing using MapReduce Hadoop, Spark (Andy Konwinski, UCB)Slides and Video
Cloud computing allows users to easily exploit large commerical compute clusters available at many companies. We discuss programming tools (eg Hadoop, MapReduce) that make them easy to use.
*3:30 - 4:00- Break
*4:00 - 5:00 - ParLab Applications: Browsers, Health, & Music (Ras Bodik, UCB; Tobias Harrison-Noonan, UCB; Nils Peters, UCB, ICSI)
Browsers:We will describe parallel algorithms for computing layout of web documents and of data visualizations. We will demonstrate a data visualization running on a GPU.Bodik's Slides, Torok's Slides
Health:Title:"Personalized Medicine from Medical Imaging and Advanced Computation".We will discuss the application of parallel computing to diagnostics of stroke patients through computational modeling.Slides
Music:Title: "A Couple Music Applications". Introduction to work being done to improve quality of service for real-time audio processing tasks, such as partitioned convolution, and to increase throughput for batch music information retrieval applications, such as drum detection.Slides