- bound thread
- distributed memory model
- Haskell thread
- A Haskell thread is a thread of execution for IO code. Multiple Haskell threads can execute IO code concurrently and they can communicate using shared mutable variables and channels.
- see spark (vs threads)
- shared memory model
- Sparks are specific to parallel Haskell. Abstractly, a spark is a pure computation which may be evaluated in parallel. Sparks are introduced with the par combinator; the expression (
x `par` y) "sparks off"
x, telling the runtime that it may evaluate the value of
xin parallel to other work. Whether or not a spark is evaluated in parallel with other computations, or other Haskell IO threads, depends on what your hardware supports and on how your program is written. Sparks are put in a work queue and when a CPU core is idle, it can execute a spark by taking one from the work queue and evaluating it.
- see spark (vs thread)
- spark (vs thread)
- On a multi-core machine, both threads and sparks can be used to achieve parallelism. Threads give you concurrent, non-deterministic parallelism, while sparks give you pure deterministic parallelism. Haskell threads are ideal for applications like network servers where you need to do lots of I/O and using concurrency fits the nature of the problem. Sparks are ideal for speeding up pure calculations where adding non-deterministic concurrency would just make things more complicated.
- OS thread
- see Haskell thread, OS thread and bound thread