Update concurrency slides

concurrency/slides.org

@@ -61,7 +61,7 @@ A second is a duration, not an instant.
 
 Two things can happen in the same second and not be simultaneous.
 
-In computer science, this nuance matters.
+With computers, this nuance matters.
 
 * 9. Time
 
@@ -98,10 +98,12 @@ Source: [[https://www.prowesscorp.com/computer-latency-at-a-human-scale/]]
 * 12. Cooking Recipes
 
 - Step-by-step
-- Concurrent
+- Concurrent:
-  - Pre-heat oven
+  - Handle other tasks while:
-  - Boil water
+    - Preheating oven
-  - Timers
+    - Boiling water
+    - Waiting for timers
+  - Switching back to a task when it is ready for more work.
 
 * 13. Multitasking
 
@@ -117,24 +119,28 @@ Computers can "simultaneously" work on:
 Combination of:
 - Operating System *Scheduler*
 - Hardware (/interrupts/)
+  - Keyboard
+  - Filesystem
+  - Network Card
+  - Timer
 
-* 17. Cooperative Scheduling
+* 16. Cooperative Scheduling
 [[file:images/cooperative-scheduling.jpg]]
 
-* 18. Preemptive Scheduling
+* 17. Preemptive Scheduling
 [[file:images/preemptive-scheduling.jpg]]
 
-* 19. Preemptive Scheduling
+* 18. Preemptive Scheduling
 [[file:images/preemptive-scheduling-tree.jpg]]
 
-* 20. Multi Core
+* 19. Multi Core
 [[file:images/preemptive-scheduling-multi-core.jpg]]
 
-* 21. Concurrency versus Parallelism
+* 20. Concurrency versus Parallelism
 
 - Parallelism :: performing computations at the same time.
   - Multiple cores.
-  - Multiples computers.
+  - Multiple computers.
   - Kind of like having multiple cooks in a kitchen.
     - Can do different things at the same time.
     - Can do one job faster (peeling a lot of potatoes).
@@ -142,13 +148,14 @@ Combination of:
 - Concurrency :: performing computations over inter-leaving, non-sequential time periods.
   - Single or multi-core.
 
-* 22. Processes and Threads
+* 21. Processes and Threads
 A little more nuance.
 
 - Different /recipes/
 - Different /parts/ of a recipe
 
 - Process :: a program in execution.
+  - Unique resources (memory, code, files, etc.).
   - Start off with one thread.
   - Can /fork/.
   - Communicate via inter-process communication (IPC).
@@ -157,17 +164,17 @@ A little more nuance.
   - Share resources ∴ less resource intensive.
   - Can communicate via shared resources.
 
-* 23. Processes and Threads
+* 22. Processes and Threads
 
 [[file:images/process-vs-thread.jpg]]
 
 Source: https://stackoverflow.com/questions/16354460/forking-vs-threading/16354658
 
-* 24. htop
+* 23. htop
 
 Press ~H~ to show threads.
 
-* 25. Languages and Runtimes
+* 24. Languages and Runtimes
 
 - ~C~, ~C++~, ~Rust~ allow for fine-grained control of processes and threads.
 #+begin_src C :output raw
@@ -180,7 +187,7 @@ int main() {
 }
 #+end_src
 
-* 26. JavaScript
+* 25. JavaScript
 - Single-threaded (for application code).
 - Runtimes implement concurrency via an event loop.
 
@@ -188,42 +195,7 @@ int main() {
 
 Source: [[https://medium.com/preezma/node-js-event-loop-architecture-go-deeper-node-core-c96b4cec7aa4]]
 
-* 27. Go
+* 26. Aside: Event Loop
-Runtime multi-threading, multiplexes goroutines onto threads.
-
-[[file:images/go-scheduler.png]]
-
-Source: https://freethreads.net/2019/01/23/go-runtime-scheduler-design-internals/
-
-* 28. Quick Review
-
-- Sequential versus Concurrent Steps
-  - Compare with recipes.
-- Concurrency versus Parallelism
-  - Parallelism: multiple cooks, simultaneously /doing/.
-  - Concurrency: one or more cooks, simultaneously /dealing/ with many tasks.
-- Operating System Scheduler
-- Processes and Threads
-- Languages and Runtimes
-
-* 29. Part 2: Using Concurrency
-
-Typical use cases:
-- Network I/O
-   - Requests between clients and servers.
-   - Requests to a database.
-   - Requests between microservices.
-   - Requests to external APIs.
-
-- User interfaces
-  - Capturing user input
-  - Rendering output
-
-- Similar, but independent computations.
-
-- Solving problems that are best expressed with concurrency.
-
-* 30. JavaScript
 
 What is the output of the following? Why?
 #+begin_src javascript
@@ -238,14 +210,49 @@ setTimeout(() => console.log('2'), 0);
 console.log('end');
 #+end_src
 
-* 31. Go Examples
+* 27. Go
+*Runtime scheduler* manages multiple threads.
+[[file:images/go-scheduler.png]]
+
+Source: https://freethreads.net/2019/01/23/go-runtime-scheduler-design-internals/
+
+* 28. Quick Review
+
+- Sequential versus Concurrent Steps
+  - Compare with recipes.
+- Concurrency versus Parallelism
+  - Parallelism: multiple cooks, simultaneously /doing/.
+  - Concurrency: one or more cooks, /dealing/ with many tasks.
+- Operating System Scheduler
+- Processes and Threads
+- Languages and Runtimes
+
+* 29. Part 2: Using Concurrency
+
+Typical use cases:
+- Network I/O between:
+   - Clients and servers.
+   - Services and database(s).
+   - Microservices.
+   - Service and external APIs.
+
+- User interfaces
+  - Capturing user input
+  - Rendering output
+
+- Similar, but independent computations.
+
+- Solving problems that are best expressed with concurrency.
+
+* 30. Go Examples
 
 1. Shared Memory with Mutex (Mutual Exclusion)
    - Pitfall: synchronization, debugging.
-2. Message Passing (Channels and Goroutines)
-   - Pitfall: resources usage, complexity.
 
-* 32. Mutex Example
+2. Message Passing (Channels and Goroutines)
+   - Pitfall: resource usage, complexity.
+
+* 31. Mutex Example
 Concurrent updates to a bank account balance.
 
 Code:
@@ -253,31 +260,37 @@ Code:
 
 Run: [[file:cmd/mutex/run.sh]]
   - Without mutex.
-  - With mutex.
 
-* 33. Data Races
+* 32. Data Races
 [[file:images/data-race.jpg]]
 
-* 34. Mutex
+* 33. Mutex
 
 /Mutual Exclusion/
 
 - Purpose: protect a critical section of code.
 - Effect: serialization.
 
-* 35. Race Detector
+Run: [[file:cmd/mutex/run.sh]]
+  - With mutex.
+
+* 34. Race Detector
+
+How can we be sure?
+
+Race detector can give us /some/ confidence (but no guarantees).
 
 - Without mutex.
 - With mutex.
 
-* 36. Tradeoffs: Validating Correctness, Testing, Debugging
+* 35. Tradeoffs: Validating Correctness, Testing, Debugging
 
 - Non-deterministic behavior
   - Works fine on one run, fatal bug in another.
   - Up to how the scheduler(s) order things at execution time.
 - Concealed bugs
 
-* 37. Message Passing
+* 36. Message Passing
 
 Proverbs:
 #+begin_quote
@@ -286,7 +299,7 @@ Don't communicate by sharing memory, share memory by communicating.
 Channels orchestrate, mutexes serialize.
 #+end_quote
 
-* 38. Requirements
+* 37. Program Requirements
 
 - Read CSV of zip codes
   - 50 in our example
@@ -298,27 +311,27 @@ Channels orchestrate, mutexes serialize.
 
 - Display running list of top ten temperatures.
 
-* 39. Concurrency Hallmarks
+* 38. Concurrency Hallmarks
 
 - Repeatedly processing similar data (lines of CSV)
 - Network I/O
 - UI I/O
 
-* 40. Message Passing Example
+* 39. Message Passing Example
 
 Run: [[file:cmd/csp/run.sh]]
 
-* 41. Code Walkthrough
+* 40. Code Walkthrough
 
 [[file:cmd/csp/main.go]]
 
-* 42. Channels and Goroutines
+* 41. Channels and Goroutines
 [[file:images/message-passing-example-diagram.jpg]]
 
-* 43. Channels and Goroutines
+* 42. Channels and Goroutines
 [[file:images/go-scheduler.jpg]]
 
-* 44. Scaling
+* 43. Scaling
 
 What if:
 - We wanted to process the entire list of 42,000 zip codes?
@@ -326,7 +339,7 @@ What if:
 
 Could we just get rid of the limiter?
 
-* 45. Resources
+* 44. Resources
 
 Probably not, because:
 
@@ -339,12 +352,12 @@ Probably not, because:
   - Better data structures and algorithms could help here.
 - Goroutines are cheap, but not free.
 
-* 46. Possible Solutions
+* 45. Possible Solutions
 
 - Use a semaphore to limit concurrency.
 - Buffers
 
-* 47. Designing and Managing Concurrency
+* 46. Designing and Managing Concurrency
 
 - Size of input matters.
 - Resources
@@ -353,7 +366,7 @@ Probably not, because:
 - Backpressure
 - Complexity
 
-* 48. Quick Review
+* 47. Quick Review
 
 Techniques for implementing and managing concurrency:
 - Event loop
@@ -367,7 +380,7 @@ Concurrency Pitfalls:
 - Complexity
   - Need to think differently about concurrent code.
 
-* 49. Part 3: Infrastructure Concurrency
+* 48. Part 3: Infrastructure Concurrency
 
 Concurrent applications running concurrently on distributed computers.
 
@@ -376,20 +389,20 @@ Concurrent applications running concurrently on distributed computers.
 - Databases
 - Host and Network Infrastructure
 
-* 50. Example
+* 49. Example
 [[file:images/infrastructure-data-race.jpg]]
 
-* 51. Review
+* 50. Review
 
 - What concurrency is
   - Sequential versus concurrent
-  - Comparison with recipes
+  - Comparison with recipes and cooks
   - Compared to parallelism
 - How it is implemented
   - Operating System Scheduler and Interrupts
   - Languages and Runtimes
 
-* 52. Review
+* 51. Review
 
 - When, why, and how to use it
   - I/O + UI
@@ -398,16 +411,16 @@ Concurrent applications running concurrently on distributed computers.
 
 - Pitfalls
   - Synchronization
-  - Resources Usage
+  - Resource Usage
   - Debugging
   - Complexity
 
-* 53. Review
+* 52. Review
 
 - Infrastructure
   - Data Race
 
-* 54. Conclusion
+* 53. Conclusion
 
 - Goals:
   - Give you a rough sense of what concurrency is.
@@ -421,7 +434,7 @@ Concurrent applications running concurrently on distributed computers.
   - Tradeoffs and economics (resources, costs, developer time).
   - Learning is continuous...
 
-* 55. Further Reading
+* 54. Further Reading
 
 - [[https://slikts.github.io/concurrency-glossary/][Concurrency Glossary]]
 - [[https://blog.golang.org/waza-talk][Concurrency is not parallelism]]