commit 69bfe6a9a92596ef6ca484383793b4d256f76355
parent 3a742253aebdcccc944b17ffdc0d9d0672d16e48
Author: dwrz <dwrz@dwrz.net>
Date: Fri, 5 Jun 2020 14:32:17 +0000
Update concurrency slides
Diffstat:
1 file changed, 62 insertions(+), 112 deletions(-)
diff --git a/concurrency/slides.org b/concurrency/slides.org
@@ -114,14 +114,8 @@ Computers can "simultaneously" work on:
* 15. How?
- Operating System's *Scheduler*
-- Hardware (interrupts)
-- Not just multiple cores!
-
-* 16. NB: Concurrency != Parallelism
-
-First consumer multi-core CPUs released in mid-2000's.
-
-Even before that, computers were able to multitask with one core.
+- Hardware
+ - /Interrupts/
* 17. Cooperative Scheduling
[[file:images/cooperative-scheduling.jpg]]
@@ -132,92 +126,75 @@ Even before that, computers were able to multitask with one core.
* 19. Preemptive Scheduling
[[file:images/preemptive-scheduling-tree.jpg]]
-* 20. Single Core
-[[file:images/single-core-concurrency.jpg]]
-
-#+begin_src bash
-strace echo "hello world"
-#+end_src
-
-* 21. Multi Core
+* 20. Multi Core
[[file:images/preemptive-scheduling-multi-core.jpg]]
-* 22. Concurrency versus Parallelism
+* 21. Concurrency versus Parallelism
- Parallelism :: performing computations at the same moment.
- Multiple cores.
- Multiples 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).
- Concurrency :: performing computations over inter-leaving, non-sequential time periods.
- Single or multi-core.
-* 23. Processes and Threads
-
-Computers can "simultaneously" work on:
+* 22. Processes and Threads
+A little more nuance.
-- Different /parts/ of a recipe
- Different /recipes/
+- Different /parts/ of a recipe
-- Process :: a program in execution (recipe).
-- Thread :: smallest sequence of programmed instructions that can be managed independently by a scheduler (part of a recipe).
-
-* 24. Processes and Threads
-
-Processes
-- Have their own memory space
- - Instructions
- - Constants
- - Stack
- - Heap
-- Start out with one thread (the /main/ thread).
-- Can fork -- create a child process.
-- Inter-Process Communication (IPC)
-
-* 25. Processes and Threads
-
-Threads (a.k.a, lightweight processes)
-
-- Share:
- - Memory
- - Instructions
- - Open files (descriptors)
- - Signals and signal handlers
- - Etcetera...
+- Process :: a program in execution.
+ - Start off with one thread.
+ - Can /fork/.
+ - Inter-Process Communication
-- Less resource intensive than processes.
+- Thread :: sequence of instructions that can be managed independently by scheduler.
+ - Share resources ∴ less resource intensive.
+ - Can communicate via shared resources.
-* 26. Processes and Threads
+* 23. Processes and Threads
[[file:images/process-vs-thread.jpg]]
Source: https://stackoverflow.com/questions/16354460/forking-vs-threading/16354658
-* 27. htop
+* 24. htop
Press ~H~ to show threads.
-* 28. Languages and Runtimes
+* 25. Languages and Runtimes
- ~C~, ~C++~, ~Rust~ allow for fine-grained control of processes and threads.
+#+begin_src C
+int main() {
+ fork();
-- ~JavaScript~: single-threaded (for your code), runtimes (Chrome, nodejs) implement concurrency via an event loop.
+ printf("Hello world!\n");
-- ~Go~: runtime multi-threading, multiplexes goroutines onto threads.
+ return 0;
+}
+#+end_src
-* 29. nodejs
+* 26. nodejs
+- Single-threaded (for application code).
+- Runtimes implement concurrency via an event loop.
[[file:images/nodejs-event-loop.png]]
Source: [[https://medium.com/preezma/node-js-event-loop-architecture-go-deeper-node-core-c96b4cec7aa4]]
-* 30. Go
+* 27. Go
+Runtime multi-threading, multiplexes goroutines onto threads.
[[file:images/go-scheduler.png]]
Source: https://freethreads.net/2019/01/23/go-runtime-scheduler-design-internals/
-* 31. Quick Review
+* 28. Quick Review
- Sequential versus Concurrent Steps
- Compare with recipes.
@@ -227,7 +204,7 @@ Source: https://freethreads.net/2019/01/23/go-runtime-scheduler-design-internals
- Processes and Threads
- Languages and Runtimes
-* 32. Part 2: Using Concurrency
+* 29. Part 2: Using Concurrency
Typical use cases:
- Network I/O
@@ -244,33 +221,29 @@ Typical use cases:
- Solving problems that are best expressed with concurrency.
-* 33. JavaScript
-
-- Callbacks
-- Promises
-- async/await
+* 30. JavaScript
What is the output of the following? Why?
#+begin_src javascript
console.log('start');
-setTimeout(() => console.log('callback 1'), 0);
+setTimeout(() => console.log('1'), 0);
console.log('middle');
-setTimeout(() => console.log('callback 2'), 0);
+setTimeout(() => console.log('2'), 0);
console.log('end');
#+end_src
-* 34. Go
+* 31. Go Examples
1. Shared Memory with Mutex (Mutual Exclusion)
- Pitfall: synchronization, debugging.
2. Message Passing (Channels and Goroutines)
- Pitfall: resources usage, complexity.
-* 35. Mutex Example
+* 32. Mutex Example
Concurrent updates to a bank account balance.
Code:
@@ -280,31 +253,29 @@ Run: [[file:cmd/mutex/run.sh]]
- Without mutex.
- With mutex.
-* 36. Data Races
+* 33. Data Races
[[file:images/data-race.jpg]]
-* 37. Mutex
+* 34. Mutex
/Mutual Exclusion/
- Purpose: protect a critical section of code.
- Effect: serialization.
-* 38. Race Detector
+* 35. Race Detector
- Without mutex.
- With mutex.
-* 39. Tradeoffs: Validating Correctness, Testing, Debugging
+* 36. 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
- - Heisenbugs
-- Deadlock and Livelock
-* 40. Message Passing
+* 37. Message Passing
Proverbs:
#+begin_quote
@@ -313,9 +284,9 @@ Don't communicate by sharing memory, share memory by communicating.
Channels orchestrate, mutexes serialize.
#+end_quote
-* 41. Requirements
+* 38. Requirements
-- Read CSV
+- Read CSV of zip codes
- 50 in our example
- Full list is ~42,000
@@ -325,27 +296,27 @@ Channels orchestrate, mutexes serialize.
- Display running list of top ten temperatures.
-* 42. Concurrency Hallmarks
+* 39. Concurrency Hallmarks
- Repeatedly processing similar data (lines of CSV)
- Network I/O
- UI I/O
-* 43. Message Passing Example
+* 40. Message Passing Example
Run: [[file:cmd/csp/run.sh]]
-* 44. Code Walkthrough
+* 41. Code Walkthrough
[[file:cmd/csp/main.go]]
-* 45. Channels and Goroutines
+* 42. Channels and Goroutines
[[file:images/message-passing-example-diagram.jpg]]
-* 46. Channels and Goroutines
+* 43. Channels and Goroutines
[[file:images/go-scheduler.jpg]]
-* 47. Scaling
+* 44. Scaling
What if:
- We wanted to process the entire list of 42,000 zip codes?
@@ -353,7 +324,7 @@ What if:
Could we just get rid of the limiter?
-* 48. Resources
+* 45. Resources
Probably not, because:
@@ -366,12 +337,12 @@ Probably not, because:
- Better data structures and algorithms could help here.
- Goroutines are cheap, but not free.
-* 49. Possible Solutions
+* 46. Possible Solutions
- Use a semaphore to limit concurrency.
- Buffers
-* 50. Designing and Managing Concurrency
+* 47. Designing and Managing Concurrency
- Size of input matters.
- Resources
@@ -380,7 +351,7 @@ Probably not, because:
- Backpressure
- Complexity
-* 51. Quick Review
+* 48. Quick Review
Techniques for implementing and managing concurrency:
- Event loop
@@ -394,7 +365,7 @@ Concurrency Pitfalls:
- Complexity
- Need to think differently about concurrent code.
-* 52. Part 3: Infrastructure Concurrency
+* 49. Part 3: Infrastructure Concurrency
Concurrent applications running concurrently on distributed computers.
@@ -403,31 +374,10 @@ Concurrent applications running concurrently on distributed computers.
- Databases
- Host and Network Infrastructure
-* 53. Student Context
-
-- Simple architectures:
- - Monolithic
- - Single DB
-- Few concurrent users
-
-* 54. Professional Context
-
-- Complex, sometimes messy architectures.
- - Containers
- - Queues
- - Workers
- - Tech Debt
- - Multiple Servers
- - Microservices
- - Multiple datastores
- - Distributed databases
-- Many concurrent users
-- Running longer (more vulnerable to failures, downtime)
-
-* 55. Example
+* 50. Example
[[file:images/infrastructure-data-race.jpg]]
-* 56. Review
+* 51. Review
- What concurrency is
- Sequential versus concurrent
@@ -437,7 +387,7 @@ Concurrent applications running concurrently on distributed computers.
- Operating System Scheduler and Interrupts
- Languages and Runtimes
-* 57. Review
+* 52. Review
- When, why, and how to use it
- I/O + UI
@@ -450,12 +400,12 @@ Concurrent applications running concurrently on distributed computers.
- Debugging
- Complexity
-* 58. Review
+* 53. Review
- Infrastructure
- Data Race
-* 59. Conclusion
+* 54. Conclusion
- Goals:
- Give you a rough sense of what concurrency is.
@@ -469,7 +419,7 @@ Concurrent applications running concurrently on distributed computers.
- Tradeoffs and economics (resources, costs, developer time).
- Learning is continuous...
-* 60. Further Reading
+* 55. Further Reading
- [[https://slikts.github.io/concurrency-glossary/][Concurrency Glossary]]
- [[https://blog.golang.org/waza-talk][Concurrency is not parallelism]]
