Dr. Jaroslaw Zola
For all email communication, please make sure to add prefix [IntroPDP] to mail subject.
This course is intended for students interested in the efficient use of modern parallel systems ranging from multi-core processors and many-core accelerators to large-scale distributed memory clusters. The course puts equal emphasis on the theoretical foundations of parallel computing, and on practical aspects of different parallel programming models. It begins with a survey of common parallel architectures and types of parallelism, and then follows with an overview of formal approaches to assess scalability and efficiency of parallel algorithms and their implementations. In the second part, the course covers the most common and current parallel programming techniques and APIs, including for shared address space, many-core accelerators and distributed memory clusters. Each component of the course involves solving practical computational and data driven problems, ranging from basic algorithms like sorting or searching, through numerical data analysis, to large graphs processing.
The course consists of a series of lectures organized into five topical modules. Each lecture module is complemented with a programming assignment exposing practical aspects of the covered material. Tentative course outline is provided below (note that individual topics within a module may get different coverage depending on how course progresses):
The course has no specific prerequisites for graduate students. For undergraduate students, CSE 220 “Systems Programming” and CSE 331 “Introduction to Algorithms” are prerequisites, as the course requires some experience in synthesis and analysis of algorithms, and programming close to the executing platform. The course has significant programming component, hence a rudimentary ability to learn new programming constructs is expected. Specifically, C++ (multi-core, many-core, MPI) and Python (Map/Reduce) will be used extensively during the course. Again, you will be expected to write non-trivial codes, however, using a fairly small subset of the respective programming languages and with APIs well covered in the course.
Please keep also in mind that all students must:
ssh, rsync, tar) and compile codes using command line interface (e.g., by calling g++).Upon completion of this course you will:
The course adopts the Student Outcomes from the Engineering Accreditation Commission of ABET (see here).
| Course Learning Outcome | Program Outcomes/Competencies | Instructional Method(s) | Assessment Method(s) |
|---|---|---|---|
| Basic understanding of fundamental concepts in parallel computing | 1: An ability to analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions | Lectures, assignments | Assignments, exams |
| Identifying and leveraging common parallel computing patterns | 2: An ability to design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline | Lectures, assignments | Assignments, exams |
| Properly assessing efficiency and scalability of a parallel algorithm/application | 6: An ability to apply computer science theory and software development fundamentals to produce computing-based solutions. | Lectures, assignments | Assignments, exams |
| Proficiency in using at least one parallel programming technique, and familiarity with several others | 2: An ability to design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program’s discipline | Lectures, assignments | Assignments, exams |
| Program Outcome | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| Support Level | 3 | 3 | 3 |
Not Supported, 1: Minimally Supported, 2: Supported, 3: Strongly Supported
The course has three requirements:
The final grade will be weighted average: 20% midterm exam, 30% final exam, 50% programming assignments. Exam and programming assignments will be the same for graduate and undergraduate students. However, criteria to decide the final grade will be different for graduate and undergraduate students. Specifically, the number-to-letter grade mapping will be done as indicated in the tables below.
Graduate
| Score | Grade | Points |
|---|---|---|
| 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 |
Undergraduate
| Score | Grade | Points |
|---|---|---|
| 93-100 | A | 4.0 |
| 85-92 | A- | 3.67 |
| 75-84 | B+ | 3.33 |
| 65-74 | B | 3.0 |
| 55-64 | B- | 2.67 |
| 50-54 | C+ | 2.33 |
| 45-49 | C | 2.00 |
| 40-44 | C- | 1.67 |
| 35-39 | D | 1 |
| 0-34 | 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).
There will be four programming assignments that will require that you develop a parallel code, test it on CCR resources, and report your findings. Assignments are graded using a combination of automated tools that test correctness and efficiency of your solution, and code review by a human to assess quality of the code. In general, the following main criteria are used for grading:
| Criterion | Comment |
|---|---|
| Correctness | Code must compile/execute and return correct answers. If code does not compile/execute it is not graded. If it is entirely correct (i.e., passes coverage tests) no points are deducted. Otherwise (i.e., it fails for some cases) points are deduced accordingly. Note also that your code must produce output exactly as specified in the assignments description. |
| Performance | It is not enough that your code gives correct answer. Your code must be efficient, and use the best possible parallel programming techniques to achieve the goal. You have to pay attention to how you solve the problem. Bad decisions are penalized. After all, parallel computing is about performance! |
| Quality | Your code cannot be a lousy last minute submission! You have to pay attention to the details. One way to think about it is that your code must be of the quality that would warrant Pull Request in a larger project. |
There are a few important factors that you must account for when it comes to assignments:
This course does not rely on one specific textbook. The following books are suggested but not required:
Before ordering any of these books, please contact your instructor regarding books availability. Additionally, several research papers may be referenced during the course.
Significant online resources, including tutorials, API documentations, “quick start guides”, etc. will be referenced during the course, and can be easily found using your favorite search engine.
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 this 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).
Thank you for upholding your own personal integrity and ensuring UB’s tradition of academic excellence.
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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