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.

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.

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.

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.

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.

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).

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.