Inverse kinematics (IK) technology helps game developers create natural character animations but its complexity makes it time consuming to implement across a large cast. This talk details how the Deep Learning Deployment Toolkit (DLDT) allows game developers to quickly deploy deep-learning algorithms to solve character IK problems and to yield better results
It Doesn't Have to Be Hard: How to Fix Your Performance WoesIntel® Software
Maximize your game performance on a wide range of hardware. Learn how to use Intel® GPA to identify and quantify common performance bottlenecks, mitigate them, and validate optimizations.
Create a Scalable and Destructible World in HITMAN 2*Intel® Software
Gain insight into how IO Interactive* (IOI) designed the crowd, environmental audio, non-playable character simulation, and physical destruction systems to take advantage of available hardware and dynamically upscale resolution and deliver more realism. See the design and architecture of the destruction system, including the asset pipeline and game runtime that enables IOI to create a more interesting world for their players.
The Architecture of 11th Generation Intel® Processor GraphicsIntel® Software
Scheduled for release this year, this next generation brings significant improvements over the widely used 9th generation of Intel® Processor Graphics. The talk begins with an overview of Intel® Graphics architecture, its building blocks, and their performance implications. Next, take an in-depth look at the new and innovative features of this latest generation of integrated graphics.
Streamed Cloud Gaming Solutions for Android* and PC GamesIntel® Software
Cloud gaming is getting a lot of press lately. As the leading cloud service provider in China, Tencent is embracing the cloud to deliver graphic-intensive PC and mobile games, as well as core developer solutions.
RenderMan*: The Role of Open Shading Language (OSL) with Intel® Advanced Vect...Intel® Software
This talk focuses on the newest release in RenderMan* 22.5 and its adoption at Pixar Animation Studios* for rendering future movies. With native support for Intel® Advanced Vector Extensions, Intel® Advanced Vector Extensions 2, and Intel® Advanced Vector Extensions 512, it includes enhanced library features, debugging support, and an extensive test framework.
It Doesn't Have to Be Hard: How to Fix Your Performance WoesIntel® Software
Maximize your game performance on a wide range of hardware. Learn how to use Intel® GPA to identify and quantify common performance bottlenecks, mitigate them, and validate optimizations.
Create a Scalable and Destructible World in HITMAN 2*Intel® Software
Gain insight into how IO Interactive* (IOI) designed the crowd, environmental audio, non-playable character simulation, and physical destruction systems to take advantage of available hardware and dynamically upscale resolution and deliver more realism. See the design and architecture of the destruction system, including the asset pipeline and game runtime that enables IOI to create a more interesting world for their players.
The Architecture of 11th Generation Intel® Processor GraphicsIntel® Software
Scheduled for release this year, this next generation brings significant improvements over the widely used 9th generation of Intel® Processor Graphics. The talk begins with an overview of Intel® Graphics architecture, its building blocks, and their performance implications. Next, take an in-depth look at the new and innovative features of this latest generation of integrated graphics.
Streamed Cloud Gaming Solutions for Android* and PC GamesIntel® Software
Cloud gaming is getting a lot of press lately. As the leading cloud service provider in China, Tencent is embracing the cloud to deliver graphic-intensive PC and mobile games, as well as core developer solutions.
RenderMan*: The Role of Open Shading Language (OSL) with Intel® Advanced Vect...Intel® Software
This talk focuses on the newest release in RenderMan* 22.5 and its adoption at Pixar Animation Studios* for rendering future movies. With native support for Intel® Advanced Vector Extensions, Intel® Advanced Vector Extensions 2, and Intel® Advanced Vector Extensions 512, it includes enhanced library features, debugging support, and an extensive test framework.
Review state-of-the-art techniques that use neural networks to synthesize motion, such as mode-adaptive neural network and phase-functioned neural networks. See how next-generation CPUs with reinforcement learning can offer better performance.
Ray Tracing with Intel® Embree and Intel® OSPRay: Use Cases and Updates | SIG...Intel® Software
Explore practical examples of Intel® Embree and Intel® OSPRay in production rendering and the best practices of using the kernels in typical rendering pipelines.
Use Variable Rate Shading (VRS) to Improve the User Experience in Real-Time G...Intel® Software
Variable-rate shading (VRS) is a new feature of Microsoft DirectX* 12 and is supported on the 11th generation of Intel® graphics hardware. Get an overview and learn best practices, recommendations, and how to modify traditional 3D effects to take advantage of VRS.
Scalability for All: Unreal Engine* 4 with Intel Intel® Software
Unreal Engine* 4 is a high-performance game engine for game developers. Learn how Intel and Epic Games* worked together to improve engine performance both for CPUs and GPUs and how developers can take advantage of it.
Advanced Single Instruction Multiple Data (SIMD) Programming with Intel® Impl...Intel® Software
Explore practical elements, such as performance profiling, debugging, and porting advice. Get an overview of advanced programming topics, like common design patterns, SIMD lane interoperability, data conversions, and more.
Build a Deep Learning Video Analytics Framework | SIGGRAPH 2019 Technical Ses...Intel® Software
Explore how to build a unified framework based on FFmpeg and GStreamer to enable video analytics on all Intel® hardware, including CPUs, GPUs, VPUs, FPGAs, and in-circuit emulators.
Open Source Interactive CPU Preview Rendering with Pixar's Universal Scene De...Intel® Software
Universal Scene Description* (USD) is an open source initiative developed by Pixar for fast, large scale, and universal asset management across multiple programs including Maya, Houdini, and others.
Tuning For Deep Learning Inference with Intel® Processor Graphics | SIGGRAPH ...Intel® Software
Deep learning based Inference on edge based devices is growing rapidly. In this talk, learn about how developers and researchers are taking advantage of Intel® Processor Graphics to get best performance.
Ultra HD Video Scaling: Low-Power HW FF vs. CNN-based Super-ResolutionIntel® Software
The visual computing world is moving to an exciting technological era of ultra HD (UHD) and wide-gamut deep colors (WCG). The new Gen9 graphics engine in the 6th generation Intel® Core™ processors is the developers’ platform choice for creating visual excellence in 4K and deep colors. The Gen9 processor graphics offers attractive solutions for high-quality and low-power video scaling that handle UHD and WCG. First, we introduce a hardware fixed-function scaler inside the new SFC (scaling and format conversion) module that provides high quality scaling in low-power platforms. Second, we present a super-resolution scaling solution based on convolutional neural network that can be implemented via OpenCL™ running on the execution units (EUs). We discuss the merits of each solution in different user environments
Embree Ray Tracing Kernels | Overview and New Features | SIGGRAPH 2018 Tech S...Intel® Software
Overview of the new Embree 3 ray tracing framework, including how to use the new API, supported geometry types, and ray intersection methods. Includes a look at new features like normal oriented curves, vertex grids, etc.
With the advent of world class engines like Unity, game development has never been easier. Developers can make deploy to multiple platforms quickly and easily, and optimize for all. Come learn to identify performance issues and their sources using Unity tools and the Intel Graphics Performance Analyzer. Along the way, we will cover some key optimization tips and Unity game development methods to keep your game fast and fantastic
Learn how to improve performance and quality of your game on Intel® Processor Graphics, including scaling from 1080p to 4k, with dynamic resolution rendering and checkerboard rendering (CBR).
Improve the performance of your Unity project using Graphics Performance Anal...Unity Technologies
This session will show you how to maximize your Unity game performance on a wide range of hardware. Learn how to use Intel Graphics Performance Analyzers (Intel GPA) to identify and quantify common performance bottlenecks, how to mitigate them, and how to validate optimizations. Using exciting new Intel GPA features, we will reveal how to gain deeper knowledge of the runtime execution of your game, easily identify problematic frames, and improve your game's overall performance.
Speaker: Valery Carpentier - Intel
Watch the session on YouTube: https://youtu.be/MzeOMK0xuac
This session discusses how to find good multiple-CPU performance with Theano* and TensorFlow*, how to extend a single-machine model with MPI, and optimize its performance as we scale out and up.
Review state-of-the-art techniques that use neural networks to synthesize motion, such as mode-adaptive neural network and phase-functioned neural networks. See how next-generation CPUs with reinforcement learning can offer better performance.
Ray Tracing with Intel® Embree and Intel® OSPRay: Use Cases and Updates | SIG...Intel® Software
Explore practical examples of Intel® Embree and Intel® OSPRay in production rendering and the best practices of using the kernels in typical rendering pipelines.
Use Variable Rate Shading (VRS) to Improve the User Experience in Real-Time G...Intel® Software
Variable-rate shading (VRS) is a new feature of Microsoft DirectX* 12 and is supported on the 11th generation of Intel® graphics hardware. Get an overview and learn best practices, recommendations, and how to modify traditional 3D effects to take advantage of VRS.
Scalability for All: Unreal Engine* 4 with Intel Intel® Software
Unreal Engine* 4 is a high-performance game engine for game developers. Learn how Intel and Epic Games* worked together to improve engine performance both for CPUs and GPUs and how developers can take advantage of it.
Advanced Single Instruction Multiple Data (SIMD) Programming with Intel® Impl...Intel® Software
Explore practical elements, such as performance profiling, debugging, and porting advice. Get an overview of advanced programming topics, like common design patterns, SIMD lane interoperability, data conversions, and more.
Build a Deep Learning Video Analytics Framework | SIGGRAPH 2019 Technical Ses...Intel® Software
Explore how to build a unified framework based on FFmpeg and GStreamer to enable video analytics on all Intel® hardware, including CPUs, GPUs, VPUs, FPGAs, and in-circuit emulators.
Open Source Interactive CPU Preview Rendering with Pixar's Universal Scene De...Intel® Software
Universal Scene Description* (USD) is an open source initiative developed by Pixar for fast, large scale, and universal asset management across multiple programs including Maya, Houdini, and others.
Tuning For Deep Learning Inference with Intel® Processor Graphics | SIGGRAPH ...Intel® Software
Deep learning based Inference on edge based devices is growing rapidly. In this talk, learn about how developers and researchers are taking advantage of Intel® Processor Graphics to get best performance.
Ultra HD Video Scaling: Low-Power HW FF vs. CNN-based Super-ResolutionIntel® Software
The visual computing world is moving to an exciting technological era of ultra HD (UHD) and wide-gamut deep colors (WCG). The new Gen9 graphics engine in the 6th generation Intel® Core™ processors is the developers’ platform choice for creating visual excellence in 4K and deep colors. The Gen9 processor graphics offers attractive solutions for high-quality and low-power video scaling that handle UHD and WCG. First, we introduce a hardware fixed-function scaler inside the new SFC (scaling and format conversion) module that provides high quality scaling in low-power platforms. Second, we present a super-resolution scaling solution based on convolutional neural network that can be implemented via OpenCL™ running on the execution units (EUs). We discuss the merits of each solution in different user environments
Embree Ray Tracing Kernels | Overview and New Features | SIGGRAPH 2018 Tech S...Intel® Software
Overview of the new Embree 3 ray tracing framework, including how to use the new API, supported geometry types, and ray intersection methods. Includes a look at new features like normal oriented curves, vertex grids, etc.
With the advent of world class engines like Unity, game development has never been easier. Developers can make deploy to multiple platforms quickly and easily, and optimize for all. Come learn to identify performance issues and their sources using Unity tools and the Intel Graphics Performance Analyzer. Along the way, we will cover some key optimization tips and Unity game development methods to keep your game fast and fantastic
Learn how to improve performance and quality of your game on Intel® Processor Graphics, including scaling from 1080p to 4k, with dynamic resolution rendering and checkerboard rendering (CBR).
Improve the performance of your Unity project using Graphics Performance Anal...Unity Technologies
This session will show you how to maximize your Unity game performance on a wide range of hardware. Learn how to use Intel Graphics Performance Analyzers (Intel GPA) to identify and quantify common performance bottlenecks, how to mitigate them, and how to validate optimizations. Using exciting new Intel GPA features, we will reveal how to gain deeper knowledge of the runtime execution of your game, easily identify problematic frames, and improve your game's overall performance.
Speaker: Valery Carpentier - Intel
Watch the session on YouTube: https://youtu.be/MzeOMK0xuac
This session discusses how to find good multiple-CPU performance with Theano* and TensorFlow*, how to extend a single-machine model with MPI, and optimize its performance as we scale out and up.
Columnar processing for SQL-on-Hadoop: The best is yet to comeWang Zuo
Apache Parquet is an open-source file-format which arranges all of its data into columns – this is distinct from the traditional row-oriented layout, which stores entire rows consecutively. Columnar data offers lots of advantages to modern data engines – like Impala, Apache Spark, and Apache Flink – in terms of IO efficiency, but the full benefits of the format are yet to be realized.
We have been working with Intel to apply modern CPU instruction sets to the common programming tasks associated with querying data in Parquet format: decompression, predicate evaluation, and row-reconstruction. Our work has yielded significant speedups in standard query benchmarks running on Cloudera’s Impala SQL query engine, and very high speedups in targeted microbenchmarks.
In this talk we’ll describe the symbiosis between modern CPU architectures and the requirements of columnar data processing. We’ll show how vectorization – processing many items with a single instruction – is a widely applicable technique that can provide real performance benefits to all application frameworks that use columnar formats. We’ll present the changes that we have made to Impala’s ‘scanner,’ which reads Parquet data, and map out even more future enhancements.
This talk will be of interest to audiences interested in the internals of big data processing engines, or the impact of recent advances in modern CPU architectures.
Mastering Multiplayer Stage3d and AIR game development for mobile devicesJean-Philippe Doiron
Video Presentation : http://tv.adobe.com/watch/max-2013/mastering-multiplayer-stage3d-and-air-game-development-for-mobile-devices/
• The use of Stage3D across web and mobile deployments (with Adobe AIR) .
• The challenges encountered when attempting to maintain high-performance specifications on mobile devices .
• Being agile in a pre production game development
• We'll show how we have jump our of the predefined sandbox to develop creative solution on well known problem.
A presentation I did for China GDC 2011.
I cover the basic of visibility optimization as well as present some practical examples of visibility systems used in modern video games.
Air Hockey Game with Google Cloud + NodeJS + NginX + Socket.io + HTML5
you can see gitlab repository: http://git.matthewlab.com/root/remote-web-airhockey
Putting a Heart into a Box:GPGPU simulation of a Cardiac Model on the Xbox 360Simon Scarle
Talk entitled "Putting a Heart into a Box:GPGPU simulation of a Cardiac Model on the Xbox 360" given by Simon Scarle at the Games for Health Conference 2010.
Getting The Most Out of VR | Sinjin BainJessica Tams
Delivered at Casual Connect Europe 2016
Virtual Reality and Augmented (or Mixed) Reality have unique and distinct capabilities from other interactive platforms that require new approaches to development and content creation and management. We will explore some innovative approaches to runtime performance, collaborative development, data and live operations to get the most out of your games in development.
Similar to Accelerate Large-Scale Inverse Kinematics with the Intel® Distribution of OpenVINO™ Toolkit (20)
AI for All: Biology is eating the world & AI is eating Biology Intel® Software
Advances in cell biology and creation of an immense amount of data are converging with advances in Machine learning to analyze this data. Biology is experiencing its AI moment and driving the massive computation involved in understanding biological mechanisms and driving interventions. Learn about how cutting edge technologies such as Software Guard Extensions (SGX) in the latest Intel Xeon Processors and Open Federated Learning (OpenFL), an open framework for federated learning developed by Intel, are helping advance AI in gene therapy, drug design, disease identification and more.
Python Data Science and Machine Learning at Scale with Intel and AnacondaIntel® Software
Python is the number 1 language for data scientists, and Anaconda is the most popular python platform. Intel and Anaconda have partnered to bring scalability and near-native performance to Python with simple installations. Learn how data scientists can now access oneAPI-optimized Python packages such as NumPy, Scikit-Learn, Modin, Pandas, and XGBoost directly from the Anaconda repository through simple installation and minimal code changes.
Streamline End-to-End AI Pipelines with Intel, Databricks, and OmniSciIntel® Software
Preprocess, visualize, and Build AI Faster at-Scale on Intel Architecture. Develop end-to-end AI pipelines for inferencing including data ingestion, preprocessing, and model inferencing with tabular, NLP, RecSys, video and image using Intel oneAPI AI Analytics Toolkit and other optimized libraries. Build at-scale performant pipelines with Databricks and end-to-end Xeon optimizations. Learn how to visualize with the OmniSci Immerse Platform and experience a live demonstration of the Intel Distribution of Modin and OmniSci.
AI for good: Scaling AI in science, healthcare, and more.Intel® Software
How do we scale AI to its full potential to enrich the lives of everyone on earth? Learn about AI hardware and software acceleration and how Intel AI technologies are being used to solve critical problems in high energy physics, cancer research, financial inclusion, and more. Get started on your AI Developer Journey @ software.intel.com/ai
Software AI Accelerators: The Next Frontier | Software for AI Optimization Su...Intel® Software
Software AI Accelerators deliver orders of magnitude performance gain for AI across deep learning, classical machine learning, and graph analytics and are key to enabling AI Everywhere. Get started on your AI Developer Journey @ software.intel.com/ai.
Advanced Techniques to Accelerate Model Tuning | Software for AI Optimization...Intel® Software
Learn about the algorithms and associated implementations that power SigOpt, a platform for efficiently conducting model development and hyperparameter optimization. Get started on your AI Developer Journey @ software.intel.com/ai.
Reducing Deep Learning Integration Costs and Maximizing Compute Efficiency| S...Intel® Software
oneDNN Graph API extends oneDNN with a graph interface which reduces deep learning integration costs and maximizes compute efficiency across a variety of AI hardware including AI accelerators. Get started on your AI Developer Journey @ software.intel.com/ai.
AWS & Intel Webinar Series - Accelerating AI ResearchIntel® Software
Scale your research workloads faster with Intel on AWS. Learn how the performance and productivity of Intel Hardware and Software help bridge the gap between ideation and results in Data Science. Get started on your AI Developer Journey @ software.intel.com/ai.
Whether you are an AI, HPC, IoT, Graphics, Networking or Media developer, visit the Intel Developer Zone today to access the latest software products, resources, training, and support. Test-drive the latest Intel hardware and software products on DevCloud, our online development sandbox, and use DevMesh, our online collaboration portal, to meet and work with other innovators and product leaders. Get started by joining the Intel Developer Community @ software.intel.com.
ANYFACE*: Create Film Industry-Quality Facial Rendering & Animation Using Mai...Intel® Software
ANYFACE* brings film industry-quality facial rendering and animation to mainstream PC platforms using novel approaches to create face details and control microsurfaces. The solution enables users to create high-fidelity game character facial models using photogrammetry.
Bring the Future of Entertainment to Your Living Room: MPEG-I Immersive Video...Intel® Software
Explore the proposed Metadata for Immersive Video (MIV) standard specification. MIV enables real-world content captured by cameras to be viewed by users with Six Degrees of Freedom (6DoF) movement, similar to a VR experience with synthetic content.
In this presentation, we describe a heuristic for modifying the structure of sparse deep convolutional networks during training. The heuristic allows us to train sparse networks directly to reach accuracies on par with accuracies obtained through compressing/pruning of big dense models. We show that exploring the network structure during training is essential to reach best accuracies, even when the optimal network structure is known a-priori.
Intel® AI: Non-Parametric Priors for Generative Adversarial Networks Intel® Software
This presentation proposes a novel prior which is derived using basic theorems from probability theory and off-the-shelf optimizers, to improve fidelity of image generation using GANs by interpolating along any Euclidean straight line without any additional training and architecture modifications
Pmemkv is an open source, key-value store for persistent memory based on the Persistent Memory Development Kit (PMDK). Written in C and C++, it provides optimized bindings for Java*, Javascript*, and Ruby on Rails*), and includes multiple storage engines for different use cases.
Big Data Uses with Distributed Asynchronous Object StorageIntel® Software
Learn about the architecture and features of Distributed Asynchronous Object Storage (DAOS). This open source object store is based on the Persistent Memory Development Kit (PMDK) for massively distributed non-volatile memory applications.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
5. @IntelSoftware @IntelGraphics 5
Inverse Kinematics (IK)
• Compute joint angle that makes end-effector move to
the target.
Target
Joint angle 3
Joint angle 1
Joint angle 2
End-effector
?
?
?
Catch the target
6. @IntelSoftware @IntelGraphics 6
Inverse Kinematics in Games
• Generate animations that interact with the
surrounding environment
ex) Solving the foot skating problem ex) Generate animation to catch some object
8. @IntelSoftware @IntelGraphics 8
Challenges
Traditional methods are not suitable for the objective
Numerical approach Analytical approach
Quality Good Bad
Performance Slow Fast
Numerical approach Analytical approach Deep Learning
Quality Good Bad Good
Performance Slow Fast Fast
Solution
9.
10. @IntelSoftware @IntelGraphics 10
Approach
“Input”
• Current Hands and Feet Positions
• Target Hands and Feet Positions
“Output”
• Climbing motion
• Number of Frames : 60
• Length : 2 seconds
Deep Learning based IK Solver
R
R
12. @IntelSoftware @IntelGraphics 12
Architecture [2/2]
Trajectory
Network
60 Pose
Networks
Curve
fitting
R
R
R
R
5 Trajectories
Smoothened
5 Trajectories
Deep Learning based IK Solver
13. @IntelSoftware @IntelGraphics 13
Gathering Training Data
1. Produce manually created “reference motion”.
2. Then randomize “start and end targets” based on “reference motion”.
3. Finally for each “start and end targets”, generate motion data using
“numerical approach”.
Random targets
Reference motion Generated motion using numerical approach
16. @IntelSoftware @IntelGraphics
① Small-sized tasks
16
CPU vs GPU [1/3] : Requirements
Inference for IK
• Small-sized neural networks
• Tasks are performed for each
game loop
• Small batch size
• Require quick response
( low–latency )
• GPU is busy rendering.
② Inference on Game-Client
Client
17. @IntelSoftware @IntelGraphics 17
CPU vs GPU [2/3] : ① Small-sized tasks
Small sized neural networks and
small batch size
Large sized neural networks and
large batch size
18. @IntelSoftware @IntelGraphics 18
CPU vs GPU [3/3] : ② Inference overhead on Game-Client
Without Inference CPU usage GPU usage Game frame rate Inference latency
No Game - - - -
Overwatch 22 % 97 % 146 fps -
PUBG 38 % 97 % 141 fps -
Assassin Creed : Odyssey 53 % 96 % 69 fps -
Inference on CPU using
Openvino CPU usage GPU usage Game frame rate Inference latency
No Game - - - 50.63ms
Overwatch 68 % ( 309.1 % ) 98 % ( 101.0 % ) 145 fps ( 99.3 % ) 57.97 ms ( 114 % )
PUBG 75 % ( 197.4 % ) 96 % ( 99.0 % ) 137 fps ( 97.2 % ) 59.92 ms ( 118 % )
Assassin Creed : Odyssey 84 % ( 158.5 % ) 96 % ( 100.0 % ) 69 fps ( 100.0 % ) 82.87 ms ( 164 % )
CPU : Intel i7-6700K GPU : Nvidia GTX 1080 ( ) : Rate of change
Inference on GPU using
Openvino
CPU usage GPU usage Game frame rate Inference latency
No Game - - - 43.87ms
Overwatch 38 % ( 172.7 % ) 97 % ( 100.0 % ) 119 fps ( 81.5 % ) 77.51 ms ( 177 % )
PUBG 66 % ( 173.7 % ) 97 % ( 100.0 % ) 113 fps ( 80.1 % ) 76.01 ms ( 173 % )
Assassin Creed : Odyssey 66 % ( 124.5 % ) 96 % ( 100.0 % ) 58 fps ( 84.1 % ) 88.93 ms ( 203 % )
19. @IntelSoftware @IntelGraphics 19
Choosing Solution for Deep Learning Inference
423.48 ms
34.75 ms
20.34 ms
2.21 ms
0
50
100
150
200
250
300
350
400
450
Naive cpp Numpy Tensorflow DL Inference Engine
Average Latency on CPU
(Lower numbers indicate better performance)
12X
faster
20X
faster
191X
faster
20. @IntelSoftware @IntelGraphics
Game Client
IK Solver
20
Introduction to Intel OpenVINO
MKL-DNN Plug-in
Inference engine
Model
Optimizer
IRTrain a
model
CPU
Deep Learning Deployment Toolkit
Deploy Pre-Trained Model
Tensorflow, Caffe, MXNet, ONNX
24. @IntelSoftware @IntelGraphics
IK Solver
24
Optimization for multiple characters [1/2]
Character
Character
Character
Character
Character
Motion timer
updates frame number.
Trajectory
Network
Pose
Network
Next frame motion data
Batch Manager
Request next frame
motion data
Next motion frame
26. @IntelSoftware @IntelGraphics 26
Finding optimal batch size that achieves maximum
throughput while maintaining limited latency
Set bs to initial batch size
Repeat until we obtain a reliable max latency
Start measuring latency
If number of inference > bs
infer multiple times
Else If number of inference <= bs
infer once and ignore unused space
Finish measuring latency
Update max latency
End
0
2
4
6
8
10
12
14
16
18
5 10 15 20 25 30 35 40 45 50
Batch size
31. @IntelSoftware @IntelGraphics 31
Deep Learning based Inverse Kinematics
§ Character animation becomes more realistic by solving IK.
§ Conventional approaches for full-body IK are complex or computationally
expensive.
§ Solving full-body IK using Intel Openvino is cost efficient and also flexible.
§ Process of “Climbing IK Solver”
1. Trajectory network
2. Curve fitting
3. Pose network
§ Gathered training data from manually crafted reference motion.
32. @IntelSoftware @IntelGraphics 32
Optimization using Intel® OpenVINO™ toolkit
§ CPU is suitable for computing inference on Game-Client.
§ Deep Learning Deployment Toolkit is high performance framework for computing
inference on a CPU.
§ Model Optimizer converts and optimizes the trained model to IR. On Game-Client,
Inference Engine loads this IR and it can now run inference on CPU using optimized
hardware plugin (MKL-DNN plugin).
§ Improved curve fitting performance by computing matrix form of cubic Hermit spline
with Inference Engine.
§ Batching inference task improves performance by parallelizing inference task by the
Inference Engine.
§ Finding optimal batch size to meet limited latency