A promising approach for debugging remote promises

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Presentation of IWST16, Prag Video: https://youtu.be/jQQqsrfRgjo

A PROMISING APPROACH
TO DEBUGGING REMOTE
PROMISES
2016
Max Leske
Andrei Chiș
Oscar Nierstrasz

DISCLAIMER

MOTIVATION

request file list
display file list
receive file list

request file list
display file list
receive file list

request file list
PROMISE
receive file list
use
use
continue

fileListPromise := [ self getFileList ] promise.
fileListPromise value.
…

request file list
what happened?

stack tracestack trace
descriptiondescription
NULLNULL
what happened?
exception object

IDEA

1
sender
receiver
1
Object
Context
CompiledMethod
1
method
Process
suspendedContext
1

sender
nil
sender
Process
suspendedContext

sender
nil
sender
Process1
suspendedContext
sender
nil
sender
Process2
suspendedContext

sender
Process1+2
suspendedContext
sender
sender
sender
sender
nil

DEMO

MEMORY

object header: 64 bits
2
pinned / immutable
slots
8
identity hash
22
format
5
class index
22
unused
2
garbage collection
3

object header
extended header
slot 0 slot 1
slot 2 …
object

object header
Context
method
closureOrNil
stackp
receiver
sender pc
16 / 56 variable slots
no extended header required
96 / 256 bytes per instance

∑ ≪ 100 000 ~ 1000
small contexts: 96 kB
large contexts: 256 kB
* 2 (reification)
small contexts: 192 kB
large contexts: 512 kB
estimated upper bounds

memory consumption of contexts:

object graph (simplified)
garbage collector
partially collected

garbage collector
not collected
copy

memory consumption of object graph:
?

PERFORMANCE

fileListPromise := [ self getFileList ] promise.
fileListPromise value.
…
copy process full copy
reify contexts

copying stack of 100 000 frames
0 MS
125 MS
250 MS
375 MS
500 MS
SMALL CONTEXTS LARGE CONTEXTS SMALL CONTEXTS LARGE CONTEXTS
with GC without GC

performance:

REMOTE
COMMUNICATION

protocol?
SeamlessSeamless

DEBUGGING
serialised process
local copy of process
proxies

THREADS
promises
events
asynchronous messages (actors)
asynchronous network requests

request file list
what happened?
copy process full copy
reify contexts
Process1+2
suspendedContext
sender
nil
sender
sender
sender
sender

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Looking to embark on a digital project in New York City? Choosing the ideal Laravel development partner is pivotal. Begin by defining your project requirements clearly. Assess potential partners' experience, expertise, and technical proficiency, checking portfolios and client testimonials. Effective communication and collaboration are paramount, so evaluate partners' communication styles and project management approaches. Consider long-term scalability and support options, and discuss pricing and contracts transparently. Lastly, trust your instincts when selecting a partner aligned with your vision and values.

How to Choose the Right Laravel Development Partner in New York City_compress...

How to Choose the Right Laravel Development Partner in New York City_compress...

How to Choose the Right Laravel Development Partner in New York City_compress...

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In an era where security concerns are paramount, the integration of artificial intelligence (AI) into CCTV cameras has revolutionized surveillance capabilities. One of the most significant advancements is the ability to achieve real-time threat detection, enabling immediate responses to potential security breaches. This blog explores how AI is reshaping surveillance through real-time threat detection and the implications of this technology.

Optimizing AI for immediate response in Smart CCTV

Optimizing AI for immediate response in Smart CCTV

Optimizing AI for immediate response in Smart CCTV

In the realm of real-time applications, Large Language Models (LLMs) have long dominated language-centric tasks, while tools like OpenCV have excelled in the visual domain. However, the future (maybe) lies in the fusion of LLMs and deep learning, giving birth to the revolutionary concept of Large Action Models (LAMs). Imagine a world where AI not only comprehends language but mimics human actions on technology interfaces. For example, the Rabbit r1 device presented at CES 2024, driven by an AI operating system and LAM, brings this vision to life. It executes complex commands, leveraging GUIs with unprecedented ease. In this presentation, join me on a journey as a software engineer tinkering with WebRTC, Janus, and LLM/LAMs. Together, we’ll evaluate the current state of these AI technologies, unraveling the potential they hold for shaping the future of real-time applications.

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Alberto González Trastoy

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Conference: Engage2024 in Antwerp Type: Workshop Speakers: Florian Vogler, Henning Kunz, Christoph Adler Title: Navigating the Future with The Hitchhiker's Guide to Notes and Domino 14 Abstract: Embark on an exhilarating journey with industry trailblazers Florian Vogler, Henning Kunz, and Christoph Adler in this not-to-be-missed workshop at the forefront of the tech universe. Get ready for a thrilling kick-off as we navigate the current state of the HCL universe, setting the stage for an exploration of the groundbreaking Notes and Domino 14. Discover the latest enhancements and revolutionary features that will redefine your experience. In this interactive session, unlock a treasure trove of tips and tricks to elevate your utilization of version 14, both with and without the game-changing panagenda MarvelClient. Brace yourself for also diving into Nomad, Nomad Web, and VoltMX, expanding your horizons in the expansive HCL landscape. Be a part of this exclusive opportunity to stay ahead in the ever-evolving world of HCL technologies. Your journey to mastering Notes and Domino 14 begins here. And remember, in the spirit of intergalactic exploration, don't forget to bring your towel!

W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...

W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...

W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...

In the past six months, the AI landscape has undergone a massive transformation, ushering in a new era of productivity with the latest in Large Language Models (LLMs) and AI technology. This deep dive unlocks how to: Create CustomGPT Models: No coding needed to tailor AI for your unique projects. Integrate your own data, including PDFs and Excel sheets, making information handling a breeze. Plus, discover how to call your own actions/integrations for even more personalized utility. Navigate Advanced Prompting: Overcome AI's memory limits and utilize Retrieval-Augmented Generation for accessing your personalized data, streamlining how you interact with AI. Stay Ahead with AI Trends: Peek into the evolving world of LLMs, featuring newcomers like Google Gemini, Anthropic Claude, Open Sora, and Twitter Grok, and understand what their advancements mean for your productivity. Witness Real-Life Transformations: Through examples and prompt demonstrations, see firsthand how these AI strategies revolutionize routine tasks, from data analysis to content creation. Learn to leverage image output and input for advanced practical use cases, adding a new dimension to your productivity toolkit. No previous coding or AI experience is needed for this talk. Stay ahead in the fast-evolving world of work. Embrace the AI revolution and transform your workflow with advanced LLM techniques. Join us to ensure you're not left behind in the productivity race.

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

VictorSzoltysek

At the recent Microsoft Ignite 2023 conference, Microsoft unveiled a groundbreaking strategy that will redefine enterprise work management. The plan involves integrating Microsoft’s key planning tools, Microsoft To Do, Microsoft Planner, and Microsoft Project for the web into a unified experience called “Microsoft Planner.” What does this new strategy from Microsoft mean for current users? Join us and learn how best to take advantage of this announcement while gaining a clear path on how to elevate the current state of Microsoft Planner from a basic task manager to a comprehensive tool for Enterprise Work Management using OnePlan. Learn how OnePlan’s integration with Microsoft Planner allows for strategic alignment with business goals through advanced features like strategic planning, portfolio management, resource management, financial management, and more!

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

OnePlan Solutions

Diamond Application Development Crafting Solutions with Precision

Diamond Application Development Crafting Solutions with Precision

Diamond Application Development Crafting Solutions with Precision

Foundation models are machine learning models which are easily capable of performing variable tasks on large and huge datasets. FMs have managed to get a lot of attention due to this feature of handling large datasets. It can do text generation, video editing to protein folding and robotics. In case we believe that FMs can help the hospitals and patients in any way, we need to perform some important evaluations, tests to test these assumptions. In this review, we take a walk through Fms and their evaluation regimes assumed clinical value. To clarify on this topic, we reviewed no less than 80 clinical FMs built from the EMR data. We added all the models trained on structured and unstructured data. We are referring to this combination of structured and unstructured EMR data or clinical data.

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

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VTU technical seminar 8Th Sem on Scikit-learn

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A Secure and Reliable Document Management System is Essential.docx

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A Secure and Reliable Document Management System is Essential.docx

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How to Choose the Right Laravel Development Partner in New York City_compress...

How to Choose the Right Laravel Development Partner in New York City_compress...

How to Choose the Right Laravel Development Partner in New York City_compress...

Optimizing AI for immediate response in Smart CCTV

Optimizing AI for immediate response in Smart CCTV

Optimizing AI for immediate response in Smart CCTV

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

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AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Diamond Application Development Crafting Solutions with Precision

Diamond Application Development Crafting Solutions with Precision

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Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

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A promising approach for debugging remote promises

1. A PROMISING APPROACH TO DEBUGGING REMOTE PROMISES 2016 Max Leske Andrei Chiș Oscar Nierstrasz

4. request file list display file list receive file list

5. request file list display file list receive file list

6. request file list PROMISE receive file list use use continue

7. fileListPromise := [ self getFileList ] promise. fileListPromise value. …

8. request file list what happened?

9. stack tracestack trace descriptiondescription NULLNULL what happened? exception object

11. 1 sender receiver 1 Object Context CompiledMethod 1 method Process suspendedContext 1

12. sender nil sender Process suspendedContext

13. sender nil sender Process1 suspendedContext sender nil sender Process2 suspendedContext

14. sender Process1+2 suspendedContext sender sender sender sender nil

17. object header: 64 bits 2 pinned / immutable slots 8 identity hash 22 format 5 class index 22 unused 2 garbage collection 3

18. object header extended header slot 0 slot 1 slot 2 … object

19. object header Context method closureOrNil stackp receiver sender pc 16 / 56 variable slots no extended header required 96 / 256 bytes per instance

20. ∑ ≪ 100 000 ~ 1000 small contexts: 96 kB large contexts: 256 kB * 2 (reification) small contexts: 192 kB large contexts: 512 kB estimated upper bounds

21. memory consumption of contexts:

22. object graph (simplified) garbage collector partially collected

23. garbage collector not collected copy

24. memory consumption of object graph: ?

25. PERFORMANCE

26. fileListPromise := [ self getFileList ] promise. fileListPromise value. … copy process full copy reify contexts

27. copying stack of 100 000 frames 0 MS 125 MS 250 MS 375 MS 500 MS SMALL CONTEXTS LARGE CONTEXTS SMALL CONTEXTS LARGE CONTEXTS with GC without GC

28. performance:

29. REMOTE COMMUNICATION

30. protocol? SeamlessSeamless

31. DEBUGGING serialised process local copy of process proxies

32. THREADS promises events asynchronous messages (actors) asynchronous network requests

33. request file list what happened? copy process full copy reify contexts Process1+2 suspendedContext sender nil sender sender sender sender