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Yarns 0.0.2 README is incomplete. Profiles: For cross-platform compatibility, yarns uses a system called 'profiles'. Before compiling, you need to generate certain files from a profile with the make-profile script. These profiles are just collections of definitions, which are used to build two files from templates - the Makefile and config.h. At present you need PHP for make-profile (rationale: I needed to put it together really quickly and PHP is the language I know best), soon this will be changed to Python. You pass the name of the profile you want to use as an argument to the make-profile script. These profiles are named [os]-[configuration]-[arch]. Available OSs: darwin (for Mac OS X) linux Available configurations: debug release Available architectures: ppc i386 x86_64 You can also from there specify additional definitions. Most of the available definitions you will not need to modify, but ones you might are to modify are: Scheduler: scheduler=NAME (name is one of the ones listed in the Schedulers section below) Synergy method: synergy=NAME (name is one of the ones listed in the Synergy methods below) Timeslice: timeslice=n (n is the standard timeslice in µs) Dead sleep time: dead_sleep_time=n (n is the dead sleep time in µs, ie the time that a processor will sleep if it has no job assigned) Stack size: stack_size=n (n is the stack size, in kb, assigned to each yarn. If this is too small, you will get very hard-to-debug problems. If this is too large, you will eat up tonnes of memory. Unless you know what you are doing, leave this at the default of 32) Schedulers: ROUND_ROBIN - a very simple round-robin scheduler, no support for priorities, just does exactly what it says on the tin STAIRCASE - rotating staircase deadline scheduler. Great all-round scheduler, particularly for applications where priorities are important. FAIR - completely fair scheduler. Great all-round scheduler, particularly where it is very important to ensure fairness between processes. Each of these schedulers will have multiple instances, one for each processing core. There is a master scheduler (the SMP scheduler) which load-balances between these. Yarns created early on with the highest priority will generally have a core allocated entirely for their use. Synergy methods: COOPERATIVE - control is specifically passed over via a call to yarn_yield MARKED - insert many calls to yarn_mark, and when the timeslice is up, this does a yield. Useful for script interpreters - insert calls at each loop iteration and before each function call in the interpreter. PREEMPTIVE - control can be passed over manually, but preemption is in place - after a set period of time, yarns are frozen and swapped out. Note that this is currently /very/ broken