16. Nondeterministic Parallel Programming
MIT OpenCourseWare
82 min, 12 sec
The video provides a detailed look into non-deterministic parallel programming, covering the complexities of determinism, mutexes, deadlock, and transactional memory.
Summary
- The video starts with the discussion of the complexities of non-deterministic parallel programming, emphasizing the challenges and the need for careful programming to avoid bugs.
- The concept of determinism in programming is explained, detailing the conditions under which a program is considered deterministic.
- Mutexes and their different types are discussed, including spinning and yielding mutexes, as well as reentrant and non-reentrant mutexes.
- Deadlock is analyzed with a focus on the dining philosophers' problem and a solution to avoid deadlock by linearly ordering resource acquisition is presented.
- Transactional memory is introduced, explaining how it can simplify concurrent graph computations by handling memory updates atomically and avoiding the need for explicit locks.
Chapter 1
The introduction outlines the course's focus on non-deterministic parallel programming and its inherent challenges.
- The course is starting to cover non-deterministic parallel programming which is described as difficult due to the issues it introduces.
- Non-determinism is characterized by the lack of a predictable execution pattern, making parallel computing more complex.
Chapter 2
An explanation of determinism in programming is provided, detailing when a program is considered deterministic.
- A program is deterministic if, on a given input, every memory location is updated with the same sequence of values in every execution.
- Different definitions of determinism are mentioned, with some focusing only on consistent output, while others require a global order of memory updates.
Chapter 3
The section emphasizes the advantages of deterministic programs, particularly in terms of debugging and repeatability.
- Deterministic programs are repeatable, which greatly aids in debugging as bugs will consistently appear upon execution.
- The discussion highlights that non-deterministic programs can lead to elusive bugs that are difficult to reproduce and fix.
Chapter 4
The section presents the golden rule of parallel programming which is to never write non-deterministic programs due to their complexity.
- The golden rule advises against writing non-deterministic parallel programs because they can exhibit anomalous behaviors and are hard to debug.
- The silver rule acknowledges that non-deterministic parallel programs may sometimes be necessary and emphasizes devising a test strategy to manage the non-determinism.
Chapter 5
Various strategies for managing non-determinism in programming are discussed, including turning off non-determinism and record-replay techniques.
- One strategy to manage non-determinism is to turn it off or control it, such as by using compiler switches that ensure deterministic memory allocation.
- Another strategy is record-replay, where a program's random elements are recorded so they can be replayed identically for debugging purposes.
- Encapsulating non-determinism within a runtime system or substituting a deterministic alternative in debug mode are also presented as viable strategies.
Chapter 6
The concept of deadlock is introduced, and the dining philosophers' problem is used to illustrate a common deadlock scenario.
- Deadlock occurs when multiple threads are waiting for resources held by each other, resulting in a system freeze.
- The dining philosophers' problem exemplifies deadlock with philosophers unable to proceed due to a circular waiting pattern for shared chopsticks (resources).
Chapter 7
Transactional memory as an alternative to explicit locks for managing concurrency is explained, with a focus on its implementation.
- Transactional memory allows regions of code to be executed atomically without specifying locks, simplifying concurrent programming.
- The implementation details of transactional memory are discussed, including the logging of memory updates, conflict resolution, and ensuring forward progress.
- The release-sort-reacquire algorithm is introduced as a novel solution for transactional memory, avoiding the need for a global lock.
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