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Text of the page (random words):
o an app when unfocused for version 1 on the phone only considering the non converged standalone phone scenario we are defining a very strict lifecycle policy all non focused apps are not guaranteed to stay in the running state and are transitioned to the not running state at the policies discretion to aggressively save resources today we are already sigstop ing app processes whenever they are unfocused and we will go even further and kill unfocused apps when we detect memory pressure even before the oom potentially kicks in why are we so strict we as a platform take on the responsibility to manage the scarce resources of a mobile device as efficiently as possible we don t want to leave it up to reviewers or users to identify and capture resource hogging apps however this is only version 1 and we consciously decided for a very conservative approach that we can open up gradually going forward as opposed to starting without a clear policy and taking away functionality over time implications of a strict lifecycle policy both internally and externally a lot of discussions have been triggered by the strict lifecycle policy for version 1 we have discussed a multitude of different use cases and almost all of them are solvable by means of separating apps into an engine and into a ui part first separating application logic from the presentation layer is good practice in software design second relying on an engine background service allows apps to escape the lifecycle trap easily by dispatching to an entity that exceeds an apps lifetime as dictated by our lifecycle policy a nice side effect is easily testable code how does work for version 1 in ubuntu touch in summary the system will provide a set of system services that cover the most prominent examples and use cases identified from both external internal discussions e g music playback in the background downloads happening in the background alarms appointments in this 1st version apps will not be able to install their own background services engines in the default setup however going forward in time we will provide a mechanism for apps to hand their engine to the system and have it executing in the background with resource constrains in place though for readers interested in more details https blueprints launchpad net ubuntu spec client 1303 add app model and lifecycle to platform api https docs google com a canonical com document d 1ij8rtpsr_eymw3mys8gu1y2cvfzpjxdmpdijigz1sca edit http ubuntu discourse org t how osx does power management and how ubuntu is competing 309 12 this entry was posted in planet ubuntu ubuntu on august 15 2013 by thomasvo5 updated mir an outpost envisioned as a new home 11 replies some time ago canonical started internal discussions about our convergence strategy clearly spelling out the distant target of shaping and developing a single computing platform and operating system that is able to power the cloud classic desktop machines laptops tv sets phones and tablets fridges anyone more to this we stated that we want a single mobile device a bundle of portable computing power together with the respective operating system that seamlessly adapts to different form factors and use cases or to put it a little more catchy your phone is your tv is your desktop is your you name it and yes we were aiming for the moon we worked hard to draft a system that would allow us to reach the moon while at the same time catering towards our other central goal of providing a beautiful and lean user experience it became apparent in conversations and discussions that one of the cornerstones of the future system we were designing will be the graphics stack including the unity shell after much discussions about existing solutions x weston and how we could leverage them we took a step back and distilled down our technical requirements for a future graphics stack tailored towards an egl gl es world minimal assumptions regarding the underlying driver model ability to leverage existing drivers implementing the android driver model ability to leverage existing hardware compositors efficient in terms of memory cpu and gpu consumption usage tightly integrated with the unity shell fulfilling the shell s requirements while at the same time not dictating any sort of semantics up the stack an efficient and secure input subsystem supporting demanding mobile use cases fully tested from the ground up adaptable to future requirements with these priorities in mind we revisited and carefully evaluated existing solutions again and found that neither of them satisfies our requirements in particular x and its driver model is way too complicated and feature laden resulting in a less efficient system and a driver model that is unlikely to be widely supported on mobile platforms in the case of weston the lack of a clearly defined driver model as well as the lack of a rigorous development process in terms of testing driven by a set of well defined requirements gave us doubts whether it would help us to reach the moon we looked further and found google s surfaceflinger a standalone compositor that fulfilled some but not all of our requirements it benefits from its consistent driver model that is widely adopted and supported within the industry and it fulfills a clear set of requirements it s rock solid and stable but we did not think that it would empower us to fulfill our mission of a tightly integrated user experience that scales across form factors however surfaceflinger was chosen as our initial solution for getting started with the overall ubuntu touch project planning to replace surfaceflinger with mir as soon as possible in summary our evaluation of existing solutions led us to the conclusion that neither of them fits our requirements and that adjusting adapting them would require substantial efforts too for this we decided to go for our own solution catering directly towards our goals and our vision effectively saying yes we are going to do our own display server the project was born and we decided to name it mir as in the space station as it would be our outpost that finally enables us to reach our goal of arriving at the moon providing a seamless and beautiful user experience spanning multiple form factors the team set off to work on mir while large parts of canonical started working on the ubuntu touch project relying on surfaceflinger a lot of knowledge and experience was and is transferred from the ubuntu touch project to the mir team with the work on the phone and tablet revealing more and more technical requirements and subtleties that heavily influenced the mir architecture and implementation thus one of the earliest technical decisions that has been taken by the team concerned the protocol that applications rely upon to communicate to mir we evaluated wayland and compared it to the surfaceflinger approach realizing that neither of them fits our needs wayland is a very promising and sensible attempt at standardizing the way that applications talk to a display server however it exposes privileged sections like the shell integration that we planned to handle differently both for security reasons and as we wanted to decouple the way the shell works on top of the display server from the application facing protocol in the end we decided to implement mir s core in a protocol agnostic way considering the communication protocol a very important part of the overall story but not the driving one we have chosen google s protocol buffers as our data and interface description language ddl idl and implemented a lean rpc layer that abstract away transport specific details relying on an ordinary socket by default it is well tested and the protobuf idl and ddl provide us with forward as well as backward versioning capabilities however the communication component of the overall system is adaptable and can be adjusted to account for future requirements and developments a final word on timelines at the time of this writing we are preparing to deploy the next version of the unity shell tightly integrated with mir in the not too distant future on the phone and the tablet however regarding the desktop use case we have integrated x leveraging the prior xwayland work to run on top of mir xmir and started initial porting efforts for toolkits with a focus on qt5 with our x integration in place you can run mir on your desktop machine if your system runs a gpu that supports the free driver stack for the closed source desktop drivers we are in active conversations with gpu vendors to enable mir on those drivers gpus too updated more to this we are working together with nvidia towards a more unified driver model sitting on top of egl as we are moving along with the development of mir we will work on integrating existing toolkits with the new display stack to allow application developers a seamless transition between different form factors and prevent them from the burden of supporting multiple different display servers as noted before qt5 is our first target here with gtk3 and xul being in the pipeline to support legacy x applications that cannot be adjusted to work against mir we will provide a translation layer that leverages the existing xmir implementation and allows legacy x apps to use mir transparently and that s pretty much it thanks for reading i hope i could give you some insight into the history of mir its motivation and its trajectory if you want to dive even further into the mir world head over to wiki ubuntu com mirspec a lot of work has already been done but more of it lies ahead of us so if you are curious have questions want to help us or simply want to get to know the team join the mir sessions at the upcoming virtual uds you might also want to read olli s description of the bigger picture including our overall convergence strategy for unity to the moon thomas this entry was posted in technology ubuntu uncategorized on march 4 2013 by thomasvo5 large scale moo experiments with shark oracle grid engine leave a reply this post explains how to conduct large scale moo experiments with the shark machine learning library on clusters running oracle grid engine an experiment consists of three phases front approximation performance indicator calculation result accumulation and statistics calculation within this post i m going to focus on the first step front approximation in this phases the pareto front approximations generated by applying multiple multi objective evolutionary algorithms moeas to a set of objective functions are recorded here i assume that we want to evaluate the µ 1 mo cma es relying on the hypervolume indicator on the dtlz suite of benchmark functions a ready to use command line application implementing the mo cma es is bundled with the default shark installation the executable is configurable via command line arguments queryable by passing help objectivefunction arg seed arg 1 storageinterval arg 100 searchspacedimension arg 10 maxnoevaluations arg 50000 timelimit arg 1000 fitnesslimit arg 1e 10 resultdir arg algorithmconfigfile arg algorithmusage defaultalgorithmusage objectivespacedimension arg 2 reportfitnessfunctions that is to execute the mo cma es for dtlz2 with 3 objectives and terminating after 50000 objective function evaluations the following call is required steadystatemocmamain objectivefunction dtlz2 objectivespacedimension 3 maxnoevaluations 50000 note that we do not specify the rng seed explicitly but rely on the default value 1 for the scenario considered here we want to run several independent trials of one specific moea and one specific objective function in parallel to this end we rely on the array job feature of the grid engine and submit an array of 25 independent trials to the grid engine with the following command qsub n dtlz2_3 t 1 25 runalgo sh dtlz2 globally known path 3 here the script runalgo sh is defined as follows bin bash s bin bash o dev null steadystatemocmamain seed sge_task_id resultdir 2 objectivefunction 1 objectivespacedimension 3 in summary the script takes care of actually running the algorithm and setting the seed to environment variable sge_task_id the variable is set by the grid engine to the unique job number and thus we can ensure independent trials there is one more thing to note the result dir needs to be known across the whole cluster normally your dev ops provide you with a scratch environment that is accessible from every computing node that s it wait a few minutes until the experiment completes and stay tuned for the second post that explains how to evaluate the quality of the pareto front approximations this entry was posted in c shark technology uncategorized on december 5 2011 by thomasvo5 µ 1 mo cma es leave a reply a brief video of the µ 1 mo cma es solving dtlz2 with 3 objectives this entry was posted in shark technology on december 2 2011 by thomasvo5 shark 3 x continuous integration leave a reply taken from the shark website shark is a modular c library for the design and optimization of adaptive systems it provides methods for linear and nonlinear optimization in particular evolutionary and gradient based algorithms kernel based learning algorithms and neural networks and various other machine learning techniques shark serves as a toolbox to support real world applications as well as research in different domains of computational intelligence and machine learning the sources are compatible with the following platforms windows solaris macos x and linux the library has been in active development for over 10 years now and is in use by scientists all over the world last year we the core shark developers decided that a rewrite of the library is necessary to support future use cases and provide a solid platform for users and contributors alike our goals were simple unify and simplify the library structure rely on established components wherever feasible documentation documentation and again documentation focus on quality in this post i would like to dive a little deeper into the topic of quality and the processes that we established to ensure a constant and high level of quality we decided to address quality both from a technical read testable and from an api point of view in terms of api quality we want the programming interface to be consistent convenient to use and easy to extend in equivalence to the user experience we want potential developers to experience a welcoming and friendly environment as we are a geographically distributed team of developers and scientists we decided to go for a pre commit code review approach implemented with the help of reviewboard despite initial concerns on behalf of the developers the review process proved to be one of the most useful tools while rewriting the library with developers starting to like the final ship it quickly in terms of technical quality we decided to go for continous integration of all reviewed commits to the rewrite branch for all of our supported platforms with the help ...
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