# CSE 603: Parallel and Distributed Processing

## Course Information

• Date/Time: MWF, 4:10-5:00pm
• Virtual: https://ub.webex.com/meet/jzola
• Delivery Mode: Remote
• Credits: 3
• CSE Focus Area: Software and Information Systems (SW)

## Instructor

Dr. Jaroslaw Zola

Department of Computer Science and Engineering

Email: jzola@buffalo.edu Web: http://www.jzola.org/ Twitter: @rzolau

For all email communication, please make sure to add prefix [PDP] to mail subject.

## Course Description

This project-based course is designed to provide practical experience in building, debugging, testing and profiling end-to-end parallel applications. Throughout the semester, students work in small teams implementing either assigned or self-proposed projects focusing on a parallel architecture of their choice (e.g., GPGPU accelerators, shared-memory servers, distributed memory bare-metal or cloud-based clusters, etc.), and using their preferred programming model (e.g., CUDA, MPI, Spark, RPC-based APIs, etc.). The course puts equal emphasis on all aspects of the project execution, all the way from the conception and background research, through implement-test-benchmark loop, all the way to the end-product deployment and demonstration. The purely practical component of the course is complemented by milestone presentations and written reports by each team, and is culminated by the full-scale product presentation at the end of the semester.

## Course Organization

The course is project based. You will form a team (and give it some cool name), and your team will work through the semester on building a parallel application. You may propose a project on which you would like to work or you may select a project from a set of projects provided by the instructor just before the beginning of the semester. Depending on your choice of the project, you will select the target parallel architecture for which you will be developing, and programming model and programming language you are going to use.

During the course, there will be three checkpoints during which you will be expected to submit written report as well as give presentation outlining your progress on the project. Specifically:

• Checkpoint 1: Summarize project on which you are going to work, summarize relevant publications that form the basis of your project. Provide description of parallel computing techniques you are going to use, demonstrate stub of code-base from which you are going to build the project.
• Checkpoint 2: Demonstrate preliminary implementation, discuss obstacles and challenges and potential mitigation plans, outline testing/benchmarking and final demonstration protocol.
• Checkpoint 3: Final report discussing your final product and results you achieved.

It is expected that you will be maintaining one document that will be evolving from checkpoint to checkpoint. At the same time, the bulk of your effort will be documented through commits to your GitHub/GitLab repository.

## Course Prerequisites

Although the course has no specific prerequisites, in order to succeed you must be already familiar with basics of parallel processing (e.g., taking CSE 470/570 “Introduction to Parallel and Distributed Processing” is highly recommended). It goes without saying that since this is project-based course the programming component will be critical to your success.

## Program Outcomes

Upon completion of this course you should be able to understand and replicate a process that goes into building an efficient parallel processing application.

## Course Requirements

The course has four requirements:

1. Checkpoint 1 Students are expected to demonstrate a high level of proficiency with the tools, techniques, algorithms, publications and potential initial source code that will form the basis of their project. The group is expected to submit and defend a roughly 5-page report surveying the space in which their project will be performed.
2. Checkpoint 2 Students are expected to provide details of their approach and show the working code prototype. A roughly 5-page report should outline the group’s proposed design, any algorithms and techniques being introduced, as well as a strategy for evaluating the resulting project against the current state of the art. Also, any encountered obstacles should be clearly identified and the mitigation strategy should be discussed.
3. Final Checkpoint Students are expected to provide a roughly 5 to 7-page report detailing their project, any summarizing all algorithms and techniques used. The report should provide detailed and extensive performance evaluation study using resources provided by CCR (addressing questions of scalability. e.g., weak/strong, and comparison against potential existing approaches).

4. Code Base Students are expected to maintain solid code-base for the duration of the project. The code should maintain a high-quality standard in terms of portability and readability such that it can be demonstrated to potential employers. The code will be reviewed systematically by the instructor.

The final grade will be assigned to the group using the weighted average: 15% report from Checkpoint 1, 15% report from Checkpoint 2, 40% report from the final Checkpoint, 30% quality of the final code. The final number-to-letter grade mapping will be done as indicated in the table below.

95-100 A 4.0
90-94 A- 3.67
80-89 B+ 3.33
70-79 B 3.0
60-69 B- 2.67
55-59 C+ 2.33
50-54 C 2.00
45-49 C- 1.67
40-44 D 1
0-39 F 0.0

In general, no incomplete grades (“IU” or “I”) will be given. However, in special circumstances that are truly beyond your control and justify incomplete grade, we will follow the university policy on incomplete grades, available here (for graduate students) and here (for undergraduate students).

## Computing Resources

For the duration of the course you will be granted access to the resources (including storage) provided by the UB Center for Computational Research (CCR). CCR is the state-of-the-art HPC and data center hosting clusters, multi-core compute nodes, and compute nodes with GPGPU accelerators. It provides programming and execution environments supporting all types of parallelism covered in this course.

Academic integrity is critical to the learning process. It is your responsibility as a student to complete your work in an honest fashion, upholding the expectations your individual instructors have for you in this regard. The ultimate goal is to ensure that you learn the content in your courses in accordance with UB’s academic integrity principles, regardless of whether instruction is in-person or remote.

You must be familiar with the university and departmental policies on academic integrity! The university policies are available from https://www.buffalo.edu/academic-integrity/policies.html. The CSE policies are available from the CSE web page.

Any violation of these policies, including but not limited to cheating on any course deliverable (e.g., homework project, exam, etc.), will result in automatic failure of the course. There will be no leniency! If you decide to use a code from some external source, e.g., an open source project, you must include a proper and clearly visible attribution in your product (it is a good idea to contact your instructor to check if the code you plan to use is admissible).

## Accessibility Resources

If you have any disability which requires reasonable accommodations to enable you to participate in this course, please contact the Office of Accessibility Resources in 60 Capen Hall, 716-645-2608 and also the instructor of this course during the first week of class. The office will provide you with information and review appropriate arrangements for reasonable accommodations, which can be found on the web at: http://www.buffalo.edu/studentlife/who-we-are/departments/accessibility.html.

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