On Thu, May 12, 2016 at 3:40 AM, Yi He <[email protected]> wrote: > Hi, Bill and Petri > > After yesterday's discussion/email I realized some strict rules in ARCH: > > 1. odp apis do not want to handle thread-to-core arrangement except > only providing availability info, right? (may be repeated several time > until I got it :)). > 2. then application needs odp-helper api to accomplish this, in other > words, odp-helper api takes the responsibility to provide methods for "odp > threads' deployment and instantiation". > > For ODP-427, narrow down the goal to "pin main thread to core 0 by > odp-helper to prevent validation tests fail, meanwhile adding no > constraints to odp apis at all", sounds good? > > Then here is the proposal: for libodphelper-linux library, add > __attribute__(constructor) constructor function to pin the main thread to > core 0. fulfil above goal and require no application code addition. (only > drawback is that cannot pin to the 1st available control thread core > because it is before odp_init_global(), no perfect world :)). >
That's an interesting suggestion. Core 0 is always a distinguished core in most systems anyway, so I don't see that as an undue restriction. We'll add this to the discussion topic list for Monday's ARCH call. > > In meanwhile we can open new thread to further discuss on the big topics: > 1, odp thread concept and their deploy and instantiation on platform. > 2, further advanced topics around (to list). > > thanks and best regards, Yi > > > On 11 May 2016 at 08:08, Bill Fischofer <[email protected]> wrote: > >> We didn't get around to discussing this during today's public call, but >> we'll try to cover this during tomorrow's ARCH call. >> >> As I noted earlier, the question of thread assignment to cores becomes >> complicated in virtual environment when it's not clear that a (virtual) >> core necessarily implies that there is any dedicated HW behind it. I think >> the simplest approach to take is simply to say that as long as the number >> of ODP threads is less than or equal to the number reported by >> odp_cpumask_all_available() and the number of control threads does not >> exceed odp_cpumask_control_default() and the number of worker threads does >> not exceed odp_cpumask_worker_default(), then the application can assume >> that each ODP thread will have its own CPU. If the thread count exceeds >> these numbers, then it is implementation-defined as to how ODP threads are >> multiplexed onto available CPUs in a fair manner. >> >> Applications that want best performance will adapt their thread usage to >> the number of CPUs available to it (subject to application-defined >> minimums, perhaps) to ensure that they don't have more threads than CPUs. >> >> If we have this convention then perhaps no additional APIs are needed to >> cover pinning/migration considerations? >> >> On Tue, May 10, 2016 at 8:04 AM, Yi He <[email protected]> wrote: >> >>> Hi, Petri >>> >>> While we can continue processor-related discussions in Bill's new >>> comprehensive email thread, about ODP-427 of how to guarantee locality of >>> odp_cpu_xxx() APIs, can we make a decision between two choices in >>> tomorrow's ARCH meeting? >>> >>> *Choice one: *constraint to ODP thread concept: every ODP thread will >>> be pinned on one CPU core. In this case, only the main thread was >>> accidentally not pinned on one core :), it is an ODP_THREAD_CONTROL, but is >>> not instantiated through odph_linux_pthread_create(). >>> >>> The solution can be: in odp_init_global() API, after >>> odp_cpumask_init_global(), pin the main thread to the 1st available core >>> for control threads. >>> >>> *Choice two: *in case to allow ODP thread migration between CPU cores, >>> new APIs are required to enable/disable CPU migration on the fly. (as patch >>> suggested). >>> >>> Let's talk in tomorrow. Thanks and Best Regards, Yi >>> >>> On 10 May 2016 at 04:54, Bill Fischofer <[email protected]> >>> wrote: >>> >>>> >>>> >>>> On Mon, May 9, 2016 at 1:50 AM, Yi He <[email protected]> wrote: >>>> >>>>> Hi, Bill >>>>> >>>>> Thanks very much for your detailed explanation. I understand the >>>>> programming practise like: >>>>> >>>>> /* Firstly developer got a chance to specify core availabilities to the >>>>> * application instance. >>>>> */ >>>>> odp_init_global(... odp_init_t *param->worker_cpus & ->control_cpus >>>>> ... ) >>>>> >>>>> *So It is possible to run an application with different core >>>>> availabilities spec on different platform, **and possible to run >>>>> multiple application instances on one platform in isolation.* >>>>> >>>>> *A: Make the above as command line parameters can help application >>>>> binary portable, run it on platform A or B requires no re-compilation, but >>>>> only invocation parameters change.* >>>>> >>>> >>>> The intent behind the ability to specify cpumasks at odp_init_global() >>>> time is to allow a launcher script that is configured by some provisioning >>>> agent (e.g., OpenDaylight) to communicate core assignments down to the ODP >>>> implementation in a platform-independent manner. So applications will fall >>>> into two categories, those that have provisioned coremasks that simply get >>>> passed through and more "stand alone" applications that will us >>>> odp_cpumask_all_available() and odp_cpumask_default_worker/control() as >>>> noted earlier to size themselves dynamically to the available processing >>>> resources. In both cases there is no need to recompile the application but >>>> rather to simply have it create an appropriate number of control/worker >>>> threads as determined either by external configuration or inquiry. >>>> >>>> >>>>> >>>>> /* Application developer fanout worker/control threads depends on >>>>> * the needs and actual availabilities. >>>>> */ >>>>> actually_available_cores = >>>>> odp_cpumask_default_worker(&cores, needs_to_fanout_N_workers); >>>>> >>>>> iterator( actually_available_cores ) { >>>>> >>>>> /* Fanout one work thread instance */ >>>>> odph_linux_pthread_create(...upon one available core...); >>>>> } >>>>> >>>>> *B: Is odph_linux_pthread_create() a temporary helper API and will >>>>> converge into platform-independent odp_thread_create(..one core spec...) >>>>> in >>>>> future? Or, is it deliberately left as platform dependant helper API?* >>>>> >>>>> Based on above understanding and back to ODP-427 problem, which seems >>>>> only the main thread (program entrance) was accidentally not pinned on one >>>>> core :), the main thread is also an ODP_THREAD_CONTROL, but was not >>>>> instantiated through odph_linux_pthread_create(). >>>>> >>>> >>>> ODP provides no APIs or helpers to control thread pinning. The only >>>> controls ODP provides is the ability to know the number of available cores, >>>> to partition them for use by worker and control threads, and the ability >>>> (via helpers) to create a number of threads of the application's choosing. >>>> The implementation is expected to schedule these threads to available cores >>>> in a fair manner, so if the number of application threads is less than or >>>> equal to the available number of cores then implementations SHOULD (but are >>>> not required to) pin each thread to its own core. Applications SHOULD NOT >>>> be designed to require or depend on any specify thread-to-core mapping both >>>> for portability as well as because what constitutes a "core" in a virtual >>>> environment may or may not represent dedicated hardware. >>>> >>>> >>>>> >>>>> A solution can be: in odp_init_global() API, after >>>>> odp_cpumask_init_global(), pin the main thread to the 1st available core >>>>> for control thread. This adds new behavioural specification to this API, >>>>> but seems natural. Actually Ivan's patch did most of this, except that the >>>>> core was fixed to 0. we can discuss in today's meeting. >>>>> >>>> >>>> An application may consist of more than a single thread at the time it >>>> calls odp_init_global(), however it is RECOMMENDED that odp_init_global() >>>> be called only from the application's initial thread and before it creates >>>> any other threads to avoid the address space confusion that has been the >>>> subject of the past couple of ARCH calls and that we are looking to achieve >>>> consensus on. I'd like to move that discussion to a separate discussion >>>> thread from this one, if you don't mind. >>>> >>>> >>>>> >>>>> Thanks and Best Regards, Yi >>>>> >>>>> On 6 May 2016 at 22:23, Bill Fischofer <[email protected]> >>>>> wrote: >>>>> >>>>>> These are all good questions. ODP divides threads into worker threads >>>>>> and control threads. The distinction is that worker threads are supposed >>>>>> to >>>>>> be performance sensitive and perform optimally with dedicated cores while >>>>>> control threads perform more "housekeeping" functions and would be less >>>>>> impacted by sharing cores. >>>>>> >>>>>> In the absence of explicit API calls, it is unspecified how an ODP >>>>>> implementation assigns threads to cores. The distinction between worker >>>>>> and >>>>>> control thread is a hint to the underlying implementation that should be >>>>>> used in managing available processor resources. >>>>>> >>>>>> The APIs in cpumask.h enable applications to determine how many CPUs >>>>>> are available to it and how to divide them among worker and control >>>>>> threads >>>>>> (odp_cpumask_default_worker() and odp_cpumask_default_control()). Note >>>>>> that ODP does not provide APIs for setting specific threads to specific >>>>>> CPUs, so keep that in mind in the answers below. >>>>>> >>>>>> >>>>>> On Thu, May 5, 2016 at 7:59 AM, Yi He <[email protected]> wrote: >>>>>> >>>>>>> Hi, thanks Bill >>>>>>> >>>>>>> I understand more deeply of ODP thread concept and in embedded app >>>>>>> developers are involved in target platform tuning/optimization. >>>>>>> >>>>>>> Can I have a little example: say we have a data-plane app which >>>>>>> includes 3 ODP threads. And would like to install and run it upon 2 >>>>>>> platforms. >>>>>>> >>>>>>> - Platform A: 2 cores. >>>>>>> - Platform B: 10 cores >>>>>>> >>>>>>> During initialization, the application can use >>>>>> odp_cpumask_all_available() to determine how many CPUs are available and >>>>>> can (optionally) use odp_cpumask_default_worker() and >>>>>> odp_cpumask_default_control() to divide them into CPUs that should be >>>>>> used >>>>>> for worker and control threads, respectively. For an application designed >>>>>> for scale-out, the number of available CPUs would typically be used to >>>>>> control how many worker threads the application creates. If the number of >>>>>> worker threads matches the number of worker CPUs then the ODP >>>>>> implementation would be expected to dedicate a worker core to each worker >>>>>> thread. If more threads are created than there are corresponding cores, >>>>>> then it is up to each implementation as to how it multiplexes them among >>>>>> the available cores in a fair manner. >>>>>> >>>>>> >>>>>>> Question, which one of the below assumptions is the current ODP >>>>>>> programming model? >>>>>>> >>>>>>> *1, *Application developer writes target platform specific code to >>>>>>> tell that: >>>>>>> >>>>>>> On platform A run threads (0) on core (0), and threads (1,2) on core >>>>>>> (1). >>>>>>> On platform B run threads (0) on core (0), and threads (1) can scale >>>>>>> out and duplicate 8 instances on core (1~8), and thread (2) on core (9). >>>>>>> >>>>>> >>>>>> As noted, ODP does not provide APIs that permit specific threads to >>>>>> be assigned to specific cores. Instead it is up to each ODP >>>>>> implementation >>>>>> as to how it maps ODP threads to available CPUs, subject to the advisory >>>>>> information provided by the ODP thread type and the cpumask assignments >>>>>> for >>>>>> control and worker threads. So in these examples suppose what the >>>>>> application has is two control threads and one or more workers. For >>>>>> Platform A you might have core 0 defined for control threads and Core 1 >>>>>> for >>>>>> worker threads. In this case threads 0 and 1 would run on Core 0 while >>>>>> thread 2 ran on Core 1. For Platform B it's again up to the application >>>>>> how >>>>>> it wants to divide the 10 CPUs between control and worker. It may want to >>>>>> have 2 control CPUs so that each control thread can have its own core, >>>>>> leaving 8 worker threads, or it might have the control threads share a >>>>>> single CPU and have 9 worker threads with their own cores. >>>>>> >>>>>> >>>>>>> >>>>>>> >>>>>> Install and run on different platform requires above platform >>>>>>> specific code and recompilation for target. >>>>>>> >>>>>> >>>>>> No. As noted, the model is the same. The only difference is how many >>>>>> control/worker threads the application chooses to create based on the >>>>>> information it gets during initialization by odp_cpumask_all_available(). >>>>>> >>>>>> >>>>>>> >>>>>>> *2, *Application developer writes code to specify: >>>>>>> >>>>>>> Threads (0, 2) would not scale out >>>>>>> Threads (1) can scale out (up to a limit N?) >>>>>>> Platform A has 3 cores available (as command line parameter?) >>>>>>> Platform B has 10 cores available (as command line parameter?) >>>>>>> >>>>>>> Install and run on different platform may not requires >>>>>>> re-compilation. >>>>>>> ODP intelligently arrange the threads according to the information >>>>>>> provided. >>>>>>> >>>>>> >>>>>> Applications determine the minimum number of threads they require. >>>>>> For most applications they would tend to have a fixed number of control >>>>>> threads (based on the application's functional design) and a variable >>>>>> number of worker threads (minimum 1) based on available processing >>>>>> resources. These application-defined minimums determine the minimum >>>>>> configuration the application might need for optimal performance, with >>>>>> scale out to larger configurations performed automatically. >>>>>> >>>>>> >>>>>>> >>>>>>> Last question: in some case like power save mode available cores >>>>>>> shrink would ODP intelligently re-arrange the ODP threads dynamically in >>>>>>> runtime? >>>>>>> >>>>>> >>>>>> The intent is that while control threads may have distinct roles and >>>>>> responsibilities (thus requiring that all always be eligible to be >>>>>> scheduled) worker threads are symmetric and interchangeable. So in this >>>>>> case if I have N worker threads to match to the N available worker CPUs >>>>>> and >>>>>> power save mode wants to reduce that number to N-1, then the only effect >>>>>> is >>>>>> that the worker CPU entering power save mode goes dormant along with the >>>>>> thread that is running on it. That thread isn't redistributed to some >>>>>> other >>>>>> core because it's the same as the other worker threads. Its is expected >>>>>> that cores would only enter power save state at odp_schedule() >>>>>> boundaries. >>>>>> So for example, if odp_schedule() determines that there is no work to >>>>>> dispatch to this thread then that might trigger the associated CPU to >>>>>> enter >>>>>> low power mode. When later that core wakes up odp_schedule() would >>>>>> continue >>>>>> and then return work to its reactivated thread. >>>>>> >>>>>> A slight wrinkle here is the concept of scheduler groups, which >>>>>> allows work classes to be dispatched to different groups of worker >>>>>> threads. In this case the implementation might want to take scheduler >>>>>> group membership into consideration in determining which cores to idle >>>>>> for >>>>>> power savings. However, the ODP API itself is silent on this subject as >>>>>> it >>>>>> is implementation dependent how power save modes are managed. >>>>>> >>>>>> >>>>>>> >>>>>>> Thanks and Best Regards, Yi >>>>>>> >>>>>> >>>>>> Thank you for these questions. I answering them I realized we do not >>>>>> (yet) have this information covered in the ODP User Guide. I'll be using >>>>>> this information to help fill in that gap. >>>>>> >>>>>> >>>>>>> >>>>>>> On 5 May 2016 at 18:50, Bill Fischofer <[email protected]> >>>>>>> wrote: >>>>>>> >>>>>>>> I've added this to the agenda for Monday's call, however I suggest >>>>>>>> we continue the dialog here as well as background. >>>>>>>> >>>>>>>> Regarding thread pinning, there's always been a tradeoff on that. >>>>>>>> On the one hand dedicating cores to threads is ideal for scale out in >>>>>>>> many >>>>>>>> core systems, however ODP does not require many core environments to >>>>>>>> work >>>>>>>> effectively, so ODP APIs enable but do not require or assume that >>>>>>>> cores are >>>>>>>> dedicated to threads. That's really a question of application design >>>>>>>> and >>>>>>>> fit to the particular platform it's running on. In embedded >>>>>>>> environments >>>>>>>> you'll likely see this model more since the application knows which >>>>>>>> platform it's being targeted for. In VNF environments, by contrast, >>>>>>>> you're >>>>>>>> more likely to see a blend where applications will take advantage of >>>>>>>> however many cores are available to it but will still run without >>>>>>>> dedicated >>>>>>>> cores in environments with more modest resources. >>>>>>>> >>>>>>>> On Wed, May 4, 2016 at 9:45 PM, Yi He <[email protected]> wrote: >>>>>>>> >>>>>>>>> Hi, thanks Mike and Bill, >>>>>>>>> >>>>>>>>> From your clear summarize can we put it into several TO-DO >>>>>>>>> decisions: (we can have a discussion in next ARCH call): >>>>>>>>> >>>>>>>>> 1. How to addressing the precise semantics of the existing >>>>>>>>> timing APIs (odp_cpu_xxx) as they relate to processor locality. >>>>>>>>> >>>>>>>>> >>>>>>>>> - *A:* guarantee by adding constraint to ODP thread concept: >>>>>>>>> every ODP thread shall be deployed and pinned on one CPU core. >>>>>>>>> - A sub-question: my understanding is that application >>>>>>>>> programmers only need to specify available CPU sets for >>>>>>>>> control/worker >>>>>>>>> threads, and it is ODP to arrange the threads onto each CPU >>>>>>>>> core while >>>>>>>>> launching, right? >>>>>>>>> - *B*: guarantee by adding new APIs to disable/enable CPU >>>>>>>>> migration. >>>>>>>>> - Then document clearly in user's guide or API document. >>>>>>>>> >>>>>>>>> >>>>>>>>> 1. Understand the requirement to have both processor-local and >>>>>>>>> system-wide timing APIs: >>>>>>>>> >>>>>>>>> >>>>>>>>> - There are some APIs available in time.h (odp_time_local(), >>>>>>>>> etc). >>>>>>>>> - We can have a thread to understand the relationship, usage >>>>>>>>> scenarios and constraints of APIs in time.h and cpu.h. >>>>>>>>> >>>>>>>>> Best Regards, Yi >>>>>>>>> >>>>>>>>> On 4 May 2016 at 23:32, Bill Fischofer <[email protected]> >>>>>>>>> wrote: >>>>>>>>> >>>>>>>>>> I think there are two fallouts form this discussion. First, >>>>>>>>>> there is the question of the precise semantics of the existing >>>>>>>>>> timing APIs >>>>>>>>>> as they relate to processor locality. Applications such as profiling >>>>>>>>>> tests, >>>>>>>>>> to the extent that they APIs that have processor-local semantics, >>>>>>>>>> must >>>>>>>>>> ensure that the thread(s) using these APIs are pinned for the >>>>>>>>>> duration of >>>>>>>>>> the measurement. >>>>>>>>>> >>>>>>>>>> The other point is the one that Petri brought up about having >>>>>>>>>> other APIs that provide timing information based on wall time or >>>>>>>>>> other >>>>>>>>>> metrics that are not processor-local. While these may not have the >>>>>>>>>> same >>>>>>>>>> performance characteristics, they would be independent of thread >>>>>>>>>> migration >>>>>>>>>> considerations. >>>>>>>>>> >>>>>>>>>> Of course all this depends on exactly what one is trying to >>>>>>>>>> measure. Since thread migration is not free, allowing such activity >>>>>>>>>> may or >>>>>>>>>> may not be relevant to what is being measured, so ODP probably wants >>>>>>>>>> to >>>>>>>>>> have both processor-local and systemwide timing APIs. We just need >>>>>>>>>> to be >>>>>>>>>> sure they are specified precisely so that applications know how to >>>>>>>>>> use them >>>>>>>>>> properly. >>>>>>>>>> >>>>>>>>>> On Wed, May 4, 2016 at 10:23 AM, Mike Holmes < >>>>>>>>>> [email protected]> wrote: >>>>>>>>>> >>>>>>>>>>> It sounded like the arch call was leaning towards documenting >>>>>>>>>>> that on odp-linux the application must ensure that odp_threads are >>>>>>>>>>> pinned >>>>>>>>>>> to cores when launched. >>>>>>>>>>> This is a restriction that some platforms may not need to make, >>>>>>>>>>> vs the idea that a piece of ODP code can use these APIs to ensure >>>>>>>>>>> the >>>>>>>>>>> behavior it needs without knowledge or reliance on the wider system. >>>>>>>>>>> >>>>>>>>>>> On 4 May 2016 at 01:45, Yi He <[email protected]> wrote: >>>>>>>>>>> >>>>>>>>>>>> Establish a performance profiling environment guarantees >>>>>>>>>>>> meaningful >>>>>>>>>>>> and consistency of consecutive invocations of the odp_cpu_xxx() >>>>>>>>>>>> APIs. >>>>>>>>>>>> While after profiling was done restore the execution >>>>>>>>>>>> environment to >>>>>>>>>>>> its multi-core optimized state. >>>>>>>>>>>> >>>>>>>>>>>> Signed-off-by: Yi He <[email protected]> >>>>>>>>>>>> --- >>>>>>>>>>>> include/odp/api/spec/cpu.h | 31 +++++++++++++++++++++++++++++++ >>>>>>>>>>>> 1 file changed, 31 insertions(+) >>>>>>>>>>>> >>>>>>>>>>>> diff --git a/include/odp/api/spec/cpu.h >>>>>>>>>>>> b/include/odp/api/spec/cpu.h >>>>>>>>>>>> index 2789511..0bc9327 100644 >>>>>>>>>>>> --- a/include/odp/api/spec/cpu.h >>>>>>>>>>>> +++ b/include/odp/api/spec/cpu.h >>>>>>>>>>>> @@ -27,6 +27,21 @@ extern "C" { >>>>>>>>>>>> >>>>>>>>>>>> >>>>>>>>>>>> /** >>>>>>>>>>>> + * @typedef odp_profiler_t >>>>>>>>>>>> + * ODP performance profiler handle >>>>>>>>>>>> + */ >>>>>>>>>>>> + >>>>>>>>>>>> +/** >>>>>>>>>>>> + * Setup a performance profiling environment >>>>>>>>>>>> + * >>>>>>>>>>>> + * A performance profiling environment guarantees meaningful >>>>>>>>>>>> and consistency of >>>>>>>>>>>> + * consecutive invocations of the odp_cpu_xxx() APIs. >>>>>>>>>>>> + * >>>>>>>>>>>> + * @return performance profiler handle >>>>>>>>>>>> + */ >>>>>>>>>>>> +odp_profiler_t odp_profiler_start(void); >>>>>>>>>>>> + >>>>>>>>>>>> +/** >>>>>>>>>>>> * CPU identifier >>>>>>>>>>>> * >>>>>>>>>>>> * Determine CPU identifier on which the calling is running. >>>>>>>>>>>> CPU numbering is >>>>>>>>>>>> @@ -170,6 +185,22 @@ uint64_t odp_cpu_cycles_resolution(void); >>>>>>>>>>>> void odp_cpu_pause(void); >>>>>>>>>>>> >>>>>>>>>>>> /** >>>>>>>>>>>> + * Stop the performance profiling environment >>>>>>>>>>>> + * >>>>>>>>>>>> + * Stop performance profiling and restore the execution >>>>>>>>>>>> environment to its >>>>>>>>>>>> + * multi-core optimized state, won't preserve meaningful and >>>>>>>>>>>> consistency of >>>>>>>>>>>> + * consecutive invocations of the odp_cpu_xxx() APIs anymore. >>>>>>>>>>>> + * >>>>>>>>>>>> + * @param profiler performance profiler handle >>>>>>>>>>>> + * >>>>>>>>>>>> + * @retval 0 on success >>>>>>>>>>>> + * @retval <0 on failure >>>>>>>>>>>> + * >>>>>>>>>>>> + * @see odp_profiler_start() >>>>>>>>>>>> + */ >>>>>>>>>>>> +int odp_profiler_stop(odp_profiler_t profiler); >>>>>>>>>>>> + >>>>>>>>>>>> +/** >>>>>>>>>>>> * @} >>>>>>>>>>>> */ >>>>>>>>>>>> >>>>>>>>>>>> -- >>>>>>>>>>>> 1.9.1 >>>>>>>>>>>> >>>>>>>>>>>> _______________________________________________ >>>>>>>>>>>> lng-odp mailing list >>>>>>>>>>>> [email protected] >>>>>>>>>>>> https://lists.linaro.org/mailman/listinfo/lng-odp >>>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> -- >>>>>>>>>>> Mike Holmes >>>>>>>>>>> Technical Manager - Linaro Networking Group >>>>>>>>>>> Linaro.org <http://www.linaro.org/> *│ *Open source software >>>>>>>>>>> for ARM SoCs >>>>>>>>>>> "Work should be fun and collaborative, the rest follows" >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>>> _______________________________________________ >>>>>>>>>>> lng-odp mailing list >>>>>>>>>>> [email protected] >>>>>>>>>>> https://lists.linaro.org/mailman/listinfo/lng-odp >>>>>>>>>>> >>>>>>>>>>> >>>>>>>>>> >>>>>>>>> >>>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
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