Fall 2021 SPO600 Weekly Schedule

This is the schedule and main index page for the SPO600 Software Portability and Optimization course for Fall 2021.

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Schedule Summary Table

This is a summary/index table. Please follow the links in each cell for additional detail which will be added below as the course proceeds -- especially for the Deliverables column.

Week	Week of...	Class I Tuesday 1:30-3:15 Room B1024	Class II Friday 11:40-1:25 Room K1263	Deliverables (Summary - click for details)
1	Jan 06	Introduction to the Course / Introduction to the Problem / How is code accepted into an open source project? (Homework: Lab 1)	Computer architecture basics / Binary Representation of Data / Introduction to Assembly Language	Set up for the course
2	Jan 13	6502 Assembly Basics Lab (Lab 2)	Math, Assembly language conventions, and Examples	Lab 1 and 2
3	Jan 20	6502 Math Lab (Lab 3)	Addressing Modes	Lab 3
4	Jan 27	Continue with Lab 3	System routines / Building Code	Lab 3
5	Feb 03	6502 String Lab (Lab 4)	Introduction to x86_64 and AArch64 architectures	Lab 4
6	Feb 10	6502 String Lab (Lab 4) Continued	x86_64 and AArch64 Assembly	Lab 4
7	Feb 17	Family Day Holiday	64-bit Assembly Language Lab (Lab 5)	Lab 5
Reading	Feb 24	Reading Week
8	Mar 02	Lab 5 Continued	Projects / Changing an Algorithm	Lab 5, Project Blogs
9	Mar 09	Algorithm Selection Lab (Lab 6)	Compiler Optimizations / SIMD and Vectorization	Lab 6
Switchover	Mar 16	Online Switchover Week
10	Mar 23	Online Startup / Project Stage 1	Review for Stage 1	Project Blogging
11	Mar 30	Quiz / Profiling	SIMD Part 1 - Autovectorization	Project Stage 1 due April 1, 11:59 pm / Blog about your project as you start Stage 2
12	Apr 06	SIMD Part 2 - Intrinsics and Inline Assembler	Good Friday Holiday	Project Stage 2 due
13	Apr 13	Quiz / Project Discussion	Wrap-up Discussion	Project Stage 3 due Monday, April 20, 11:59 pm (Firm!)

Week 1

Week 1 - Class I

Introduction to the Problems

Porting and Portability

• Most software is written in a high-level language which can be compiled into machine code for a specific computer architecture. In many cases, this code can be compiled for multiple architectures. However, there is a lot of existing code that contains some architecture-specific code fragments written in architecture-specific high-level code or in Assembly Language.
• Reasons that code is architecture-specific:
  • System assumptions that don't hold true on other platforms
    • Variable or word size
    • Endianness
  • Code that takes advantage of platform-specific features
• Reasons for writing code in Assembly Langauge include:
  • Performance
  • Atomic Operations
  • Direct access to hardware features, e.g., CPUID registers
• Most of the historical reasons for including assembler are no longer valid. Modern compilers can out-perform most hand-optimized assembly code, atomic operations can be handled by libraries or compiler intrinsics, and most hardware access should be performed through the operating system or appropriate libraries.
• A new architecture has appeared: AArch64, which is part of ARMv8. This is the first new computer architecture to appear in several years (at least, the first mainstream computer architecture).
• At this point, most key open source software (the software typically present in a Linux distribution such as Ubuntu or Fedora, for example) now runs on AArch64. However, it may not run as well as on older architectures (such as x86_64).

Benchmarking and Profiling

Benchmarking involves testing software performance under controlled conditions so that the performance can be compared to other software, the same software operating on other types of computers, or so that the impact of a change to the software can be gauged.

Profiling is the process of analyzing software performance on finer scale, determining resource usage per program part (typically per function/method). This can identify software bottlenecks and potential targets for optimization.

Optimization

Optimization is the process of evaluating different ways that software can be written or built and selecting the option that has the best performance tradeoffs.

Optimization may involve substituting software algorithms, altering the sequence of operations, using architecture-specific code, or altering the build process. It is important to ensure that the optimized software produces correct results and does not cause an unacceptable performance regression for other use-cases, system configurations, operating systems, or architectures.

The definition of "performance" varies according to the target system and the operating goals. For example, in some contexts, low memory or storage usage is important; in other cases, fast operation; and in other cases, low CPU utilization or long battery life may be the most important factor. It is often possible to trade off performance in one area for another; using a lookup table, for example, can reduce CPU utilization and improve battery life in some algorithms, in return for increased memory consumption.

Most advanced compilers perform some level of optimization, and the options selected for compilation can have a significant effect on the trade-offs made by the compiler, affecting memory usage, execution speed, executable size, power consumption, and debuggability.

Build Process

Building software is a complex task that many developers gloss over. The simple act of compiling a program invokes a process with five or more stages, including pre-proccessing, compiling, optimizing, assembling, and linking. However, a complex software system will have hundreds or even thousands of source files, as well as dozens or hundreds of build configuration options, auto configuration scripts (cmake, autotools), build scripts (such as Makefiles) to coordinate the process, test suites, and more.

The build process varies significantly between software packages. Most software distribution projects (including Linux distributions such as Ubuntu and Fedora) use a packaging system that further wraps the build process in a standardized script format, so that different software packages can be built using a consistent process.

In order to get consistent and comparable benchmark results, you need to ensure that the software is being built in a consistent way. Altering the build process is one way of optimizing software.

Note that the build time for a complex package can range up to hours or even days!

General Course Information

• Course resources are linked from the CDOT wiki, starting at https://wiki.cdot.senecacollege.ca/wiki/SPO600 (Quick find: This page will usually be Google's top result for a search on "SPO600").
• Coursework is submitted by blogging.
• Quizzes will be short (1 page) and will be held without announcement at any time, generally at the start of class. There is no opportunity to re-take a missed quiz, but your lowest three quiz scores will not be counted, so do not worry if you miss one or two.
  • Students with test accommodations: an alternate monthly quiz is available in the Test Centre. See the professor for details.
• Course marks (see Weekly Schedule for dates):
  • 60% - Project Deliverables
  • 20% - Communication (Blog and Wiki writing)
  • 20% - Labs and Quizzes (10% labs - completed/not completed; 10% for quizzes - lowest 3 scores not counted)
• Classes will be held in an Active Learning Classroom -- you are encouraged to bring your own laptop to class. If you do not have a laptop, consider signing one out of the Learning Commons for class, or using a smartphone with an HDMI adapter.
• For more course information, refer to the SPO600 Weekly Schedule (this page), the Course Outline, and SPO600 Course Policies.

Course and Setup: Accounts, agreements, servers, and more

• SPO600 Communication Tools
• Winter 2020 SPO600 Participants page
• Key generation for SSH to the SPO600 Servers.

How open source communities work

• Do the Code Review Lab (Lab 1) as homework.