A nice property of logic programming is that its semantics don't depend on "time": it just turns data into data (unlike "imperative" programming, like C, Java, etc. which rely on state changing over time). This is why logic programming is sometimes called "declarative".
Whilst concurrency and parallelism are a bit of a nightmare in imperative languages (e.g. multithreading), they turn out to be trivial in such "declarative" languages; in fact the difficulty is usually in reducing parallelism, to keep down the context-switching overheads.
Traditional logic programming languages like Prolog work in a single-threaded depth-first manner, i.e. to execute something like `main` we look at its definition, which might have multiple "clauses" depending on the input data (a bit like doing a `switch` or `cond` to figure out what to return); Prolog will see if the first condition applies, and if so it will start calculating the corresponding definition, which will probably involve some mixture of calls to other functions; it will execute those functions in a similar way. However, it will also "remember where it got up to" during the execution of 'main'; if the definition fails (or if we've asked for more than one result!), it will "back track" and try the next clause. This sort of like having a try/catch in each switch clause, and moving on to the next clause if there's an exception.
Strand seems similar, but rather than trying one clause at a time, depth-first; it instead runs all of the clauses concurrently. This doesn't need to "remember" anything or back-track; if a particular clause fails then its thread dies, leaving the others (if any) to keep going.
It seems like a remarkably simple way to achieve massive parallelism, especially for those already familiar with logic programming.
Whilst concurrency and parallelism are a bit of a nightmare in imperative languages (e.g. multithreading), they turn out to be trivial in such "declarative" languages; in fact the difficulty is usually in reducing parallelism, to keep down the context-switching overheads.
Traditional logic programming languages like Prolog work in a single-threaded depth-first manner, i.e. to execute something like `main` we look at its definition, which might have multiple "clauses" depending on the input data (a bit like doing a `switch` or `cond` to figure out what to return); Prolog will see if the first condition applies, and if so it will start calculating the corresponding definition, which will probably involve some mixture of calls to other functions; it will execute those functions in a similar way. However, it will also "remember where it got up to" during the execution of 'main'; if the definition fails (or if we've asked for more than one result!), it will "back track" and try the next clause. This sort of like having a try/catch in each switch clause, and moving on to the next clause if there's an exception.
Strand seems similar, but rather than trying one clause at a time, depth-first; it instead runs all of the clauses concurrently. This doesn't need to "remember" anything or back-track; if a particular clause fails then its thread dies, leaving the others (if any) to keep going.
It seems like a remarkably simple way to achieve massive parallelism, especially for those already familiar with logic programming.