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@@ -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
* 22. Processes and Threads
A little more nuance.
Computers can "simultaneously" work on:
- 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).
- Process :: a program in execution.
- Start off with one thread.
- Can /fork/.
- Inter-Process Communication
* 24. Processes and Threads
- Thread :: sequence of instructions that can be managed independently by scheduler.
- Share resources ∴ less resource intensive.
- Can communicate via shared resources.
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...
- Less resource intensive than processes.
* 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]]