SS-CPSIoT 2023_Kevin Mika and Piotr Zierhoffer presentationVEDLIoT Project
VEDLIoT – Accelerated AIoT. Kevin Mika and Piotr Zierhoffer. CPS&IoT’2023 Summer School on Cyber-Physical Systems and Internet-of-Things, Budva, Montenegro, June 2023
VEDLIOT – Accelerated AIoT. Jens Hagemeyer. 2nd Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2023, Toulouse, France, January 2023
VEDLIoT – A heterogeneous hardware platform for next-gen AIoT applications, Jens Hagemeyer, EU-IoT Training Session on “Machine Learning at the Edge and the FarEdge”, IoT Week (online event), August 2021
EU-IoT Training Workshops Series: AIoT and Edge Machine Learning 2021_Jens Ha...VEDLIoT Project
IoT - Accelerated Deep Learning for Cognitive Edge Computing, Jens Hagemeyer, EU-IoT Training Workshops Series – “AIoT and Edge Machine Learning”, May 2021
The number of internet-connected devices is growing exponentially, enabling an increasing number of edge applications in environments such as smart cities, retail, and industry 4.0. These intelligent solutions often require processing large amounts of data, running models to enable image recognition, predictive analytics, autonomous systems, and more. Increasing system workloads and data processing capacity at the edge is essential to minimize latency, improve responsiveness, and reduce network traffic back to data centers. Purpose-built systems such as Supermicro’s short-depth, multi-node SuperEdge, powered by 3rd Gen Intel® Xeon® Scalable processors, increase compute and I/O density at the edge and enable businesses to further accelerate innovation.
Join this webinar to discover new insights in edge-to-cloud infrastructures and learn how Supermicro SuperEdge multi-node solutions leverage data center scale, performance, and efficiency for 5G, IoT, and Edge applications.
The document outlines an agenda for a presentation on the VEDLIoT project. The agenda includes an introduction to VEDLIoT by Pedro Trancoso, a presentation on VEDLIoT Hardware Platforms by Kevin Mika, and a discussion of Performance Evaluation and Benchmarking in VEDLIoT by Mario Pormann. The VEDLIoT project aims to develop very efficient deep learning techniques for IoT applications through the use of heterogeneous hardware platforms and accelerators.
SS-CPSIoT 2023_Kevin Mika and Piotr Zierhoffer presentationVEDLIoT Project
VEDLIoT – Accelerated AIoT. Kevin Mika and Piotr Zierhoffer. CPS&IoT’2023 Summer School on Cyber-Physical Systems and Internet-of-Things, Budva, Montenegro, June 2023
VEDLIOT – Accelerated AIoT. Jens Hagemeyer. 2nd Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2023, Toulouse, France, January 2023
VEDLIoT – A heterogeneous hardware platform for next-gen AIoT applications, Jens Hagemeyer, EU-IoT Training Session on “Machine Learning at the Edge and the FarEdge”, IoT Week (online event), August 2021
EU-IoT Training Workshops Series: AIoT and Edge Machine Learning 2021_Jens Ha...VEDLIoT Project
IoT - Accelerated Deep Learning for Cognitive Edge Computing, Jens Hagemeyer, EU-IoT Training Workshops Series – “AIoT and Edge Machine Learning”, May 2021
The number of internet-connected devices is growing exponentially, enabling an increasing number of edge applications in environments such as smart cities, retail, and industry 4.0. These intelligent solutions often require processing large amounts of data, running models to enable image recognition, predictive analytics, autonomous systems, and more. Increasing system workloads and data processing capacity at the edge is essential to minimize latency, improve responsiveness, and reduce network traffic back to data centers. Purpose-built systems such as Supermicro’s short-depth, multi-node SuperEdge, powered by 3rd Gen Intel® Xeon® Scalable processors, increase compute and I/O density at the edge and enable businesses to further accelerate innovation.
Join this webinar to discover new insights in edge-to-cloud infrastructures and learn how Supermicro SuperEdge multi-node solutions leverage data center scale, performance, and efficiency for 5G, IoT, and Edge applications.
The document outlines an agenda for a presentation on the VEDLIoT project. The agenda includes an introduction to VEDLIoT by Pedro Trancoso, a presentation on VEDLIoT Hardware Platforms by Kevin Mika, and a discussion of Performance Evaluation and Benchmarking in VEDLIoT by Mario Pormann. The VEDLIoT project aims to develop very efficient deep learning techniques for IoT applications through the use of heterogeneous hardware platforms and accelerators.
White Box Hardware Challenges in the 5G & IoT Hyperconnected EraCharo Sanchez
The development of an agile mobile network that supports a massive number of connected devices, low latencies, broadband speeds, network slicing, and edge intelligence is the result of a number of technologies that form the 5G vision. Advantech 5G Edge Servers and Universal Edge Appliances have been designed for the network edge to meet high availability network needs providing an open virtual infrastructure for seamless network transformation toward cloud native 5G architectures. From SD-WAN and private networks to virtual RAN, Central Office and Edge Cloud, Advantech is enabling the co-creation of products and services that will form the backbone of the new 5G & IoT economy.
www.advantech.com/nc/spotlight/5G
Intels presentation at blue line industrial computer seminarBlue Line
This document provides an overview of Intel Corporation in 2014. It discusses Intel's mission to bring smart, connected devices to everyone using Moore's Law. Over 75% of Intel's business is outside the US, with key focus areas including data center, client, ultra-mobile, and wearables/IoT. Intel has a track record of executing Moore's Law and developing new process technologies like 14nm. The document outlines Intel's various business groups and labs focusing on areas like the internet of things. It provides a roadmap for Intel gateways for IoT and discusses Intel's history and position as the world's largest semiconductor manufacturer.
AccML, co-located with HiPEAC 2021_Pedro Trancoso presentationVEDLIoT Project
VEDLIoT is a project that aims to develop a framework for the next generation internet of things (IoT) based on IoT devices that collaboratively solve complex deep learning applications across distributed systems. The project will improve the performance and cost ratio of AI processing by distributing hardware across the entire chain from embedded devices to the cloud. It will also increase the safety, health and well-being of users through accelerating AI methods for user-home interaction. The project will develop a cognitive IoT platform, deep learning toolchain, and DL accelerators to enable this vision over its three year timeline starting in November 2020.
This document outlines the curriculum for an IoT and embedded systems training program. It covers topics such as embedded C, microcontrollers, sensors, communication protocols, cloud computing, IoT architectures, edge computing, machine learning, and industry use cases. Live use cases and projects are also included to provide hands-on experience with developing end-to-end IoT solutions. The training is offered at multiple levels from introductory to advanced, with longer durations covering more in-depth material.
The Considerations for Internet of Things @ 2017Jian-Hong Pan
物聯網是一門透過通訊,將端點蒐集到的資料,集中關聯分析,並將分析結果用以決策並回饋的工程藝術。
本次的分享將從物聯網的目的當作進入點,接著分享可能的佈署架構。並概述目前各個常用的通訊標準、協定,以及其所屬的角色。
除此之外,也會分享去年到柏林參加Linux Foundation舉辦的Open IoT Summit Europe 2016的心得。
在此,帶回一些國外對於物聯網節點的佈署、更新或維護的看法、作法。
另外,也會分享一些物聯網可能需要考量的資訊安全議題。
IoT is a kind of engineering art, which analyzes the collected data from
the device nodes through the communication and has the result for the
decision making and feedback.
This sharing goes for the purpose of IoT and it's deployment structure.
Then, the slide introduces the most used communication standards or
protocols in IoT and their roles.
Besides, also shares what I have got from the Open IoT Summit Europe 2016
which was held by Linux Foundation in Berlin last year.
It introduces how will the device nodes be deployed, updated and maintained.
Finally, the slide provides some security issues that should be considered
in IoT.
The document discusses Cisco's Field Area Network solution including:
- Multi-service connectivity using smart endpoints, fog computing, security, management, and standards
- The DevNet and Solution Partner Program focusing on technology, partner stories, and participation levels
- Cisco's approach to enabling IoT applications including open standards, security, management, and providing application capabilities at the network edge
A session in the DevNet Zone at Cisco Live, Berlin. Flare allows users with mobile devices to discover and interact with things in an environment. It combines multiple location technologies, such as iBeacon and CMX, with a realtime communications architecture to enable new kinds of user interactions. This session will introduce the Flare REST and Socket.IO API, server, client libraries and sample code, and introduce you to the resources available on DevNet and GitHub. Come visit us in the DevNet zone for a hands-on demonstration.
Introduction to the new MediaTek LinkIt™ Development Platform for RTOSMediaTek Labs
The new MediaTek LinkIt™ Development Platform for RTOS is based on ARM Cortex-M4 MCU architecture and provides leading features for the creation of connected appliances, home and office automation devices, smart gadgets, and IoT bridges. Supporting a range of chipsets (initially the MediaTek MT7687F), LinkIt for RTOS offers the convenience of a single toolset and common API implemented over a popular RTOS. With this you can achieve economies across a full range of consumer and business IoT devices. The platform consists of a Software Development Kit (SDK), Hardware Development Kits (HDKs), including modules from supply chain partners, and related technical documentation. The first release of the platform supports the MediaTek MT7687F Wi-Fi SOC which has a 192 MHz MCU, 1×1 802.11b/g/n Wi-Fi subsystem, integrated security engine (AES and 3DES/SHA), embedded SRAM/ROM and 2MB flash. The new platform uses FreeRTOS with open-source modules for TCP/IP, SSL/TLS, HTTP (client and server), SNTP, DHCP daemon, MQTT, XML and JSON. Development and debugging is supported by free command line tools, plus a KEIL plug-in.
This document provides an overview of the NIO100 IoT Gateway product from NEXCOM. It describes the key features of the NIO100 including its Intel Quark processor, support for multiple communication protocols, embedded IoT Studio gateway builder software, rugged design, and modular connectivity options. It also outlines several example applications and provides marketing support services available for the NIO100 product.
Open Source Possibilities for 5G Edge Computing DeploymentIgnacio Verona
This document discusses open source possibilities for 5G edge computing deployment using OpenStack NFV, OpenShift edge container engine, and Ceph data lake. It outlines a shift from centralized core data centers to decentralized edge and core architectures with geo-replicated container registries. This allows distributing virtualized network functions (VNFs) and containerized network functions (CNFs) across the edge and core. It also discusses using the telco edge to access technologies on an OpenStack NFV platform to bring user traffic into cloud-native apps in Kubernetes at the edge. Finally, it provides examples of potential 5G and multi-access edge computing use cases and discusses challenges for communication service providers in managing this new infrastructure.
VEDLIoT at FPL'23_Accelerators for Heterogenous Computing in AIoTVEDLIoT Project
VEDLIoT took part in the 33rd International Conference on Field-Programmable Logic and Applications (FPL 2023), in Gothenburg, Sweden. René Griessl (UNIBI) presented VEDLIoT and our latest achievements in the Research Projects Event session, giving a presentation entitled "Accelerators for Heterogenous Computing in AIoT".
Xilinx provides adaptable acceleration platforms for data centers. Their Alveo product lineup includes the U280, U250, U200, and low-profile U50 accelerator cards. The cards feature FPGAs with up to 1.3 million logic cells and high-speed memory. Xilinx also offers the U25 SmartNIC which combines an FPGA, ARM CPU, and dual 25GbE ports. These platforms accelerate workloads such as AI, databases, storage, and networking using reconfigurable and adaptable hardware. Xilinx supports deployment from their devices to cloud platforms using a unified software stack.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2022/06/the-future-of-ai-is-here-today-deep-dive-into-qualcomms-on-device-ai-offerings-a-presentation-from-qualcomm/
Vinesh Sukumar, Senior Director and Head of AI/ML Product Management at Qualcomm, presents the “Future of AI is Here Today: Deep Dive into Qualcomm’s On-Device AI Offerings” tutorial at the May 2022 Embedded Vision Summit.
As a leader in on-device AI, Qualcomm is in a unique position to deliver optimized and now personalized AI experiences to consumers, made possible via innovation in hardware technology and investment across the entire software stack. This investment is now deeply rooted in all of our product offerings, spread across multiple verticals from mobile to automotive.
In this talk, Sukumar explores the high-performance, low-power Hexagon processor — the core of his company’s latest 7th Generation AI Engine — and shows how the company scales it across the range of products that Qualcomm offers. He also highlights Qualcomm’s investment in advanced techniques such as the latest quantization approaches and neural architecture search to accelerate AI deployment. Finally, he shares details on how his company incorporates these technologies into AI solutions that power Qualcomm’s vision of on-device AI — and shows how these solutions are employed in real-world use cases across many verticals.
The document discusses how FPGAs from Lattice Semiconductor can accelerate edge AI applications. It notes that on-device AI inference is growing rapidly at the edge due to latency, security, and bandwidth limitations. FPGAs offer scalable and flexible performance for multiple use cases, secure configuration, hardware programmability to adapt to changing algorithms, and ultra-low power consumption from 1mW to 1W. Lattice's FPGAs allow parallel processing to improve FPS for AI tasks while reducing power compared to other solutions. The document provides examples of edge applications and Lattice's software and development tools to optimize AI models for implementation on their FPGA platforms.
The document discusses industrial Internet of Things (IIoT). It describes how ARM technology spans from sensors to servers, enabling embedded intelligence from low-power devices to infrastructure. IIoT allows for greater visibility, analytics capabilities, and coordination of industrial processes. Key takeaways are that IIoT is applications spanning the physical and cloud environments using IP connectivity to the edge, treating devices as web services, and following standards. IIoT drives operational efficiency through situational awareness, predictive maintenance, and other benefits.
IoT is a green field of new business opportunities. The ran has started…..
Everyware Device Cloud (EDC) is a full set of Operational Technologies available also as a service, which represent the fastest way to start an IoT business.
You can connect a Device to Cloud in 15 minutes.
With EDC A typical IoT project would take 2 to 6 months to go live and the ROI is really fast
.
Industrial IoT Mayhem? Java IoT Gateways to the RescueEurotech
Industrial IoT comes with great expectations for operational efficiency, promising improved asset utilization and productivity gains. IIoT challenges include reliability, security, low maintenance, long lifecycle, and integration into heterogeneous and fragmented systems. This session proposes some architectural patterns that can be leveraged to overcome these challenges. It introduces, at the center of the solution, Java-powered IoT gateways and modular IoT application frameworks such as the open source Eclipse Kura. Incorporating a live demonstration, the presentation highlights some of the latest Eclipse Kura features such as a pluggable device model for fieldbus protocols, visual data flow, and connectivity across various IoT cloud service providers.
JavaOne 2016 - Presentation by Dave Woodard and Walt Bowers
Embedded Fest 2019. Dov Nimratz. Artificial Intelligence in Small Embedded Sy...EmbeddedFest
Majority of IoT solutions use data analysis at the Cloud level, collecting a huge amount of raw data from many thousands of peripherals. What if I told you that you can move from raw data collection to knowledge aggregation by implementing Artificial Intelligence into IoT systems?
During the talk, I will show the benefits of introducing AI at the earliest possible stages, applying the concept of moving from Cloud computing to Fog computing. The basic principle of constructing AIoT systems is the use of the node logic, where a node of the system has to process the provided information in a form of abstract concepts, but not in a form of raw information.
Further, the experience of one device learning and the history of its life cycle can be applied to new models, automatically programming their production cycles for the most efficient use. Actually, IoT solutions should apply AI components at each level of data transfer. Following this approach, the whole system becomes self-optimizing.
Also, during the talk, I will present related case studies and demonstrate a working stand.
IoT Tech Expo 2023_Micha vor dem Berge presentationVEDLIoT Project
VEDLIoT Next Generation AIoT Applications. Micha vor dem Berge. VEDLIoT Conference Track co-located with IoT Tech Expo, Amsterdam, Netherlands, September 2023
Next generation accelerated AIoT systems and applications. Pedro Trancoso. Special Session on EU Projects, co-located with Computing Frontiers 2023, Bologna, Italy, May 2023
More Related Content
Similar to NGIoT standardisation workshops_Jens Hagemeyer presentation
White Box Hardware Challenges in the 5G & IoT Hyperconnected EraCharo Sanchez
The development of an agile mobile network that supports a massive number of connected devices, low latencies, broadband speeds, network slicing, and edge intelligence is the result of a number of technologies that form the 5G vision. Advantech 5G Edge Servers and Universal Edge Appliances have been designed for the network edge to meet high availability network needs providing an open virtual infrastructure for seamless network transformation toward cloud native 5G architectures. From SD-WAN and private networks to virtual RAN, Central Office and Edge Cloud, Advantech is enabling the co-creation of products and services that will form the backbone of the new 5G & IoT economy.
www.advantech.com/nc/spotlight/5G
Intels presentation at blue line industrial computer seminarBlue Line
This document provides an overview of Intel Corporation in 2014. It discusses Intel's mission to bring smart, connected devices to everyone using Moore's Law. Over 75% of Intel's business is outside the US, with key focus areas including data center, client, ultra-mobile, and wearables/IoT. Intel has a track record of executing Moore's Law and developing new process technologies like 14nm. The document outlines Intel's various business groups and labs focusing on areas like the internet of things. It provides a roadmap for Intel gateways for IoT and discusses Intel's history and position as the world's largest semiconductor manufacturer.
AccML, co-located with HiPEAC 2021_Pedro Trancoso presentationVEDLIoT Project
VEDLIoT is a project that aims to develop a framework for the next generation internet of things (IoT) based on IoT devices that collaboratively solve complex deep learning applications across distributed systems. The project will improve the performance and cost ratio of AI processing by distributing hardware across the entire chain from embedded devices to the cloud. It will also increase the safety, health and well-being of users through accelerating AI methods for user-home interaction. The project will develop a cognitive IoT platform, deep learning toolchain, and DL accelerators to enable this vision over its three year timeline starting in November 2020.
This document outlines the curriculum for an IoT and embedded systems training program. It covers topics such as embedded C, microcontrollers, sensors, communication protocols, cloud computing, IoT architectures, edge computing, machine learning, and industry use cases. Live use cases and projects are also included to provide hands-on experience with developing end-to-end IoT solutions. The training is offered at multiple levels from introductory to advanced, with longer durations covering more in-depth material.
The Considerations for Internet of Things @ 2017Jian-Hong Pan
物聯網是一門透過通訊,將端點蒐集到的資料,集中關聯分析,並將分析結果用以決策並回饋的工程藝術。
本次的分享將從物聯網的目的當作進入點,接著分享可能的佈署架構。並概述目前各個常用的通訊標準、協定,以及其所屬的角色。
除此之外,也會分享去年到柏林參加Linux Foundation舉辦的Open IoT Summit Europe 2016的心得。
在此,帶回一些國外對於物聯網節點的佈署、更新或維護的看法、作法。
另外,也會分享一些物聯網可能需要考量的資訊安全議題。
IoT is a kind of engineering art, which analyzes the collected data from
the device nodes through the communication and has the result for the
decision making and feedback.
This sharing goes for the purpose of IoT and it's deployment structure.
Then, the slide introduces the most used communication standards or
protocols in IoT and their roles.
Besides, also shares what I have got from the Open IoT Summit Europe 2016
which was held by Linux Foundation in Berlin last year.
It introduces how will the device nodes be deployed, updated and maintained.
Finally, the slide provides some security issues that should be considered
in IoT.
The document discusses Cisco's Field Area Network solution including:
- Multi-service connectivity using smart endpoints, fog computing, security, management, and standards
- The DevNet and Solution Partner Program focusing on technology, partner stories, and participation levels
- Cisco's approach to enabling IoT applications including open standards, security, management, and providing application capabilities at the network edge
A session in the DevNet Zone at Cisco Live, Berlin. Flare allows users with mobile devices to discover and interact with things in an environment. It combines multiple location technologies, such as iBeacon and CMX, with a realtime communications architecture to enable new kinds of user interactions. This session will introduce the Flare REST and Socket.IO API, server, client libraries and sample code, and introduce you to the resources available on DevNet and GitHub. Come visit us in the DevNet zone for a hands-on demonstration.
Introduction to the new MediaTek LinkIt™ Development Platform for RTOSMediaTek Labs
The new MediaTek LinkIt™ Development Platform for RTOS is based on ARM Cortex-M4 MCU architecture and provides leading features for the creation of connected appliances, home and office automation devices, smart gadgets, and IoT bridges. Supporting a range of chipsets (initially the MediaTek MT7687F), LinkIt for RTOS offers the convenience of a single toolset and common API implemented over a popular RTOS. With this you can achieve economies across a full range of consumer and business IoT devices. The platform consists of a Software Development Kit (SDK), Hardware Development Kits (HDKs), including modules from supply chain partners, and related technical documentation. The first release of the platform supports the MediaTek MT7687F Wi-Fi SOC which has a 192 MHz MCU, 1×1 802.11b/g/n Wi-Fi subsystem, integrated security engine (AES and 3DES/SHA), embedded SRAM/ROM and 2MB flash. The new platform uses FreeRTOS with open-source modules for TCP/IP, SSL/TLS, HTTP (client and server), SNTP, DHCP daemon, MQTT, XML and JSON. Development and debugging is supported by free command line tools, plus a KEIL plug-in.
This document provides an overview of the NIO100 IoT Gateway product from NEXCOM. It describes the key features of the NIO100 including its Intel Quark processor, support for multiple communication protocols, embedded IoT Studio gateway builder software, rugged design, and modular connectivity options. It also outlines several example applications and provides marketing support services available for the NIO100 product.
Open Source Possibilities for 5G Edge Computing DeploymentIgnacio Verona
This document discusses open source possibilities for 5G edge computing deployment using OpenStack NFV, OpenShift edge container engine, and Ceph data lake. It outlines a shift from centralized core data centers to decentralized edge and core architectures with geo-replicated container registries. This allows distributing virtualized network functions (VNFs) and containerized network functions (CNFs) across the edge and core. It also discusses using the telco edge to access technologies on an OpenStack NFV platform to bring user traffic into cloud-native apps in Kubernetes at the edge. Finally, it provides examples of potential 5G and multi-access edge computing use cases and discusses challenges for communication service providers in managing this new infrastructure.
VEDLIoT at FPL'23_Accelerators for Heterogenous Computing in AIoTVEDLIoT Project
VEDLIoT took part in the 33rd International Conference on Field-Programmable Logic and Applications (FPL 2023), in Gothenburg, Sweden. René Griessl (UNIBI) presented VEDLIoT and our latest achievements in the Research Projects Event session, giving a presentation entitled "Accelerators for Heterogenous Computing in AIoT".
Xilinx provides adaptable acceleration platforms for data centers. Their Alveo product lineup includes the U280, U250, U200, and low-profile U50 accelerator cards. The cards feature FPGAs with up to 1.3 million logic cells and high-speed memory. Xilinx also offers the U25 SmartNIC which combines an FPGA, ARM CPU, and dual 25GbE ports. These platforms accelerate workloads such as AI, databases, storage, and networking using reconfigurable and adaptable hardware. Xilinx supports deployment from their devices to cloud platforms using a unified software stack.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2022/06/the-future-of-ai-is-here-today-deep-dive-into-qualcomms-on-device-ai-offerings-a-presentation-from-qualcomm/
Vinesh Sukumar, Senior Director and Head of AI/ML Product Management at Qualcomm, presents the “Future of AI is Here Today: Deep Dive into Qualcomm’s On-Device AI Offerings” tutorial at the May 2022 Embedded Vision Summit.
As a leader in on-device AI, Qualcomm is in a unique position to deliver optimized and now personalized AI experiences to consumers, made possible via innovation in hardware technology and investment across the entire software stack. This investment is now deeply rooted in all of our product offerings, spread across multiple verticals from mobile to automotive.
In this talk, Sukumar explores the high-performance, low-power Hexagon processor — the core of his company’s latest 7th Generation AI Engine — and shows how the company scales it across the range of products that Qualcomm offers. He also highlights Qualcomm’s investment in advanced techniques such as the latest quantization approaches and neural architecture search to accelerate AI deployment. Finally, he shares details on how his company incorporates these technologies into AI solutions that power Qualcomm’s vision of on-device AI — and shows how these solutions are employed in real-world use cases across many verticals.
The document discusses how FPGAs from Lattice Semiconductor can accelerate edge AI applications. It notes that on-device AI inference is growing rapidly at the edge due to latency, security, and bandwidth limitations. FPGAs offer scalable and flexible performance for multiple use cases, secure configuration, hardware programmability to adapt to changing algorithms, and ultra-low power consumption from 1mW to 1W. Lattice's FPGAs allow parallel processing to improve FPS for AI tasks while reducing power compared to other solutions. The document provides examples of edge applications and Lattice's software and development tools to optimize AI models for implementation on their FPGA platforms.
The document discusses industrial Internet of Things (IIoT). It describes how ARM technology spans from sensors to servers, enabling embedded intelligence from low-power devices to infrastructure. IIoT allows for greater visibility, analytics capabilities, and coordination of industrial processes. Key takeaways are that IIoT is applications spanning the physical and cloud environments using IP connectivity to the edge, treating devices as web services, and following standards. IIoT drives operational efficiency through situational awareness, predictive maintenance, and other benefits.
IoT is a green field of new business opportunities. The ran has started…..
Everyware Device Cloud (EDC) is a full set of Operational Technologies available also as a service, which represent the fastest way to start an IoT business.
You can connect a Device to Cloud in 15 minutes.
With EDC A typical IoT project would take 2 to 6 months to go live and the ROI is really fast
.
Industrial IoT Mayhem? Java IoT Gateways to the RescueEurotech
Industrial IoT comes with great expectations for operational efficiency, promising improved asset utilization and productivity gains. IIoT challenges include reliability, security, low maintenance, long lifecycle, and integration into heterogeneous and fragmented systems. This session proposes some architectural patterns that can be leveraged to overcome these challenges. It introduces, at the center of the solution, Java-powered IoT gateways and modular IoT application frameworks such as the open source Eclipse Kura. Incorporating a live demonstration, the presentation highlights some of the latest Eclipse Kura features such as a pluggable device model for fieldbus protocols, visual data flow, and connectivity across various IoT cloud service providers.
JavaOne 2016 - Presentation by Dave Woodard and Walt Bowers
Embedded Fest 2019. Dov Nimratz. Artificial Intelligence in Small Embedded Sy...EmbeddedFest
Majority of IoT solutions use data analysis at the Cloud level, collecting a huge amount of raw data from many thousands of peripherals. What if I told you that you can move from raw data collection to knowledge aggregation by implementing Artificial Intelligence into IoT systems?
During the talk, I will show the benefits of introducing AI at the earliest possible stages, applying the concept of moving from Cloud computing to Fog computing. The basic principle of constructing AIoT systems is the use of the node logic, where a node of the system has to process the provided information in a form of abstract concepts, but not in a form of raw information.
Further, the experience of one device learning and the history of its life cycle can be applied to new models, automatically programming their production cycles for the most efficient use. Actually, IoT solutions should apply AI components at each level of data transfer. Following this approach, the whole system becomes self-optimizing.
Also, during the talk, I will present related case studies and demonstrate a working stand.
Similar to NGIoT standardisation workshops_Jens Hagemeyer presentation (20)
IoT Tech Expo 2023_Micha vor dem Berge presentationVEDLIoT Project
VEDLIoT Next Generation AIoT Applications. Micha vor dem Berge. VEDLIoT Conference Track co-located with IoT Tech Expo, Amsterdam, Netherlands, September 2023
Next generation accelerated AIoT systems and applications. Pedro Trancoso. Special Session on EU Projects, co-located with Computing Frontiers 2023, Bologna, Italy, May 2023
IoT Week 2022-NGIoT session_Micha vor dem Berge presentationVEDLIoT Project
This document discusses optimizing a smart home system using edge computing and machine learning. It describes using embedded accelerators like the Nvidia Jetson AGX and Xavier to distribute neural networks and machine learning models to devices around the home. These include a smart mirror, kitchen, door, and other devices. The goal is to optimize the models to increase energy efficiency and distribute the workloads across the edge devices. One focus is developing a smart mirror prototype that can recognize faces, objects and gestures using embedded accelerators like the t.RECS and u.RECS boards to analyze camera input and interact with users through voice and a virtual display.
Next Generation IoT Architectures_Hans SalomonssonVEDLIoT Project
VEDLIoT Toolchain for Efficient Deep Learning on heterogeneous hardware, Hans Salomonsson, EU-IoT Training Workshops Series – "Next Generation IoT Architectures”, November 2021
The document discusses hardware platforms and accelerators for VEDLIoT. It describes the VEDLIoT Hardware Platform as a heterogeneous, modular, and scalable microserver system that supports the IoT spectrum from embedded to edge to cloud. It then provides details on several platforms: the RECS|Box platform which uses Computer-on-Module standards to achieve flexibility and performance; the t.RECS platform optimized for local edge applications; and the uRECS embedded device platform that supports machine learning acceleration and communication interfaces. Diagrams and specifications are given for the architectures of these platforms.
VEDLIoT Cognitive IoT Hardware Platform. René Griessl. Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2022, Budapest, Hungary, June 2022
Security for VEDLIoT Components, from Cloud through Edge to IoT. Marcelo Pasin. Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2022, Budapest, Hungary, June 2022
Security and Robustness for VEDLIoT Components, from Cloud through Edge. Marcelo Pasin. VEDLIoT Conference Track co-located with IoT Tech Expo, Amsterdam, Netherlands, September 2023
Reconfigurable ML Accelerators in VEDLIoT. Marco Tassemeier. Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2022, Budapest, Hungary, June 2022
HiPEAC2022-DL4IoT workshop_ Muhammad Waqar AzharVEDLIoT Project
Co-design of DL Accelerators in VEDLIoT. Muhammad Waqar Azhar. Workshop on Deep Learning for IoT (DL4IoT), co-located with HiPEAC 2022, Budapest, Hungary, June 2022.
The document discusses VEDLIoT, a project that aims to develop very efficient deep learning for IoT applications. It focuses on developing a scalable and heterogeneous hardware platform using accelerators like FPGAs and ASICs. The project also aims to optimize deep learning toolchains for IoT use cases in industries like industrial IoT, automotive, and smart homes. An open call was announced to allow early use and evaluation of the VEDLIoT technology.
just download it to see!
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Towards Wearable Continuous Point-of-Care Monitoring for Deep Vein Thrombosis...ThrombUS+ Project
Kaldoudi E, Marozas M, Jurkonis R, Pousset N, Legros M, Kircher M, Novikov D, Sakalauskas A, Moustakidis P, Ayinde B, Moltani LA, Balling S, Vehkaoja A, Oksala N, Macas A, Balciuniene N, Bigaki M, Potoupnis M, Papadopoulou S-L, Grandone E, Gautier M, Bouda S, Schloetelburg C, Prinz T, Dionisio P, Anagnostopoulos S, Drougka I, Folkvord F, Drosatos G, Didaskalou S and the ThrombUS+ Consortium, Towards Wearable Continuous Point-of-Care Monitoring for Deep Vein Thrombosis of the Lower Limb. In: Jarm, T., Šmerc, R., Mahnič-Kalamiza, S. (eds) 9th European Medical and Biological Engineering Conference. EMBEC 2024. IFMBE Proceedings, vol 113. Springer, Cham. https://doi.org/10.1007/978-3-031-61628-0_36
Presented by Dr. Stelios Didaskalou, ThrombUS+ Project Manager
ScieNCE grade 08 Lesson 1 and 2 NLC.pptxJoanaBanasen1
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Detecting visual-media-borne disinformation: a summary of latest advances at ...VasileiosMezaris
We present very briefly some of the most important and latest (June 2024) advances in detecting visual-media-borne disinformation, based on the research work carried out at the Intelligent Digital Transformation Laboratory (IDT Lab) of CERTH-ITI.
Prototype Implementation of Non-Volatile Memory Support for RISC-V Keystone E...LenaYu2
Handling confidential information has become an increasingly important concern among many areas of society. However, current computing environments have been still vulnerable to various threats, and we should think they are untrusted.
Trusted Execution Environments (TEEs) have attracted attention because they can execute a program in a trusted environment constructed on an untrusted platform.
Particularly, the RISC-V Keystone is one of the interesting TEEs since it is a flexibly customizable and fully open-source platform. On the other hand, as same as other TEEs, it must also delegate I/O processing, such as file accesses, to a host OS, resulting in the expensive overhead. For this problem, we thought utilizing byte-addressable non-volatile memory (NVM) modules is a useful solution to handle persistent data objects for TEEs.
In this paper, we introduce a prototype implementation of NVM support for the Keystone. Additionally, we evaluate it on the Freedom U500 built on a VC707 FPGA dev kit.
https://ken.ieice.org/ken/paper/20210720TC4K/
Detecting and translating language ambiguity with multilingual LLMsBehrang Mehrparvar
Language is one of the most important landmarks in humans in history. However, most languages could be ambiguous, which means the same conveyed text or speech, results in different actions by different readers or listeners. In this project we propose a method to detect the ambiguity of a sentence using translation by multilingual LLMs. In this context, we hypothesize that a good machine translator should preserve the ambiguity of sentences in all target languages. Therefore, we investigate whether ambiguity is encoded in the hidden representation of a translation model or, instead, if only a single meaning is encoded. The potential applications of the proposed approach span i) detecting ambiguous sentences, ii) fine-tuning existing multilingual LLMs to preserve ambiguous information, and iii) developing AI systems that can generate ambiguity-free languages when needed.
Measuring gravitational attraction with a lattice atom interferometerSérgio Sacani
Despite being the dominant force of nature on large scales, gravity remains relatively
elusive to precision laboratory experiments. Atom interferometers are powerful tools
for investigating, for example, Earth’s gravity1
, the gravitational constant2
, deviations
from Newtonian gravity3–6
and general relativity7
. However, using atoms in free fall
limits measurement time to a few seconds8
, and much less when measuring
interactions with a small source mass2,5,6,9
. Recently, interferometers with atoms
suspended for 70 s in an optical-lattice mode fltered by an optical cavity have been
demonstrated10–14. However, the optical lattice must balance Earth’s gravity by
applying forces that are a billionfold stronger than the putative signals, so even tiny
imperfections may generate complex systematic efects. Thus, lattice interferometers
have yet to be used for precision tests of gravity. Here we optimize the gravitational
sensitivity of a lattice interferometer and use a system of signal inversions to suppress
and quantify systematic efects. We measure the attraction of a miniature source mass
to be amass = 33.3 ± 5.6stat ± 2.7syst nm s−2, consistent with Newtonian gravity, ruling out
‘screened ffth force’ theories3,15,16 over their natural parameter space. The overall
accuracy of 6.2 nm s−2 surpasses by more than a factor of four the best similar
measurements with atoms in free fall5,6
. Improved atom cooling and tilt-noise
suppression may further increase sensitivity for investigating forces at sub-millimetre
ranges17,18, compact gravimetry19–22, measuring the gravitational Aharonov–Bohm
efect9,23 and the gravitational constant2
, and testing whether the gravitational feld
has quantum properties24.
CYTOCHROME P-450 BASED DRUG INTERACTION.pptxPRAMESHPANWAR1
Cytochrome P450 (CYP) enzymes are a large family of heme-containing enzymes found primarily in the liver. They play a critical role in the metabolism of a wide variety of substances, including drugs, toxins, and endogenous compounds such as hormones and fatty acids. The name "P450" comes from the absorption peak at 450 nm when the enzyme is bound to carbon monoxide. These enzymes facilitate oxidation reactions, which often make substances more water-soluble and easier to excrete from the body.
CYP enzymes are involved in numerous drug interactions due to their ability to metabolize medications. These interactions can lead to altered drug levels, resulting in either reduced efficacy or increased toxicity. Key CYP enzymes include CYP3A4, CYP2D6, CYP2C9, CYP2C19, and CYP1A2, each responsible for the metabolism of different drugs.
But in this slide share, we only study the drug interaction of the cytochrome P450 enzyme.
Understanding the function and interactions of CYP enzymes is essential in pharmacology to ensure safe and effective drug therapy.
It also includes the mechanisms of drug interaction, i.e., enzyme inhibition and enzyme induction, with proper examples and explained in easy language.
I hope you find it useful.
Thank you so much..
2. 2
Platform
Hardware: Scalable, heterogeneous, distributed
Accelerators: Efficiency boost by FPGA and ASIC technology
Toolchain: Optimizing Deep Learning for IoT
Use cases
Industrial IoT
Automotive
Smart Home
Open call
10 projects covering a wide range of AIoT applications
Early use and evaluation of VEDLIoT technology
Very Efficient Deep Learning for IoT –
VEDLIoT
Call: H2020-ICT2020-1
Topic: ICT-56-2020 Next Generation Internet of Things
Duration: 1. November 2020 – 31. Oktober 2023
Coordinator: Bielefeld University (Germany)
Overall budget: 7 996 646.25 €
Consortium: 12 partners from 4 EU countries (Germany,
Poland, Portugal and Sweden) and one associated
country (Switzerland).
More info:
https://www.vedliot.eu/
https://twitter.com/VEDLIoT
https://www.linkedin.com/company/vedliot/
4. 4
VEDLIoT Hardware Platform
Heterogeneous, modular, scalable microserver system
Supporting the full spectrum of IoT from embedded over the edge towards the cloud
Different technology concepts for improving
x86
GPU
ML-ASIC
ARM v8
GPU
SoC
FPGA
SoC
RISC-V
FPGA
VEDLIOT Cognitive
IoT Platform
Performance
Cost-effectiveness
Maintainability
Reliability
Energy-Efficiency
Safety
5. 5
RECS Architecture – RECS|BOX
RECS Server Backplane (up to 15 Carriers)
Carrier (PCIe Expansion)
Carrier (High Performance)
e.g. GPU-Accelerator
Carrier (Low Power)
#3
#2
Microserver
(High Performance)
#1
Microserver
(Low Power)
#16
#3
#2
Microserver
(Low Power)
#1
High-Speed Low-Latency Network (PCIe, High-Speed Serial)
Compute Network (up to 40 GbE)
Management Network (KVM, Monitoring, …)
HDMI/USB
iPass+ HD
QSFP+
RJ45
Ext. Connectors
GPU
SoC
FPGA
SoC
ARM
Soc
Low-Power Microserver
(Apalis/Jetson)
x86 ARM v8
High-Performance Microserver (COM
Express)
FPGA SoC
High-Performance
Carrier
(up to 3 microservers)
Low-Power Carrier
(up to 16 microservers)
6. 6
t.RECS
t.RECS Edge Server
Optimized platform for
local / edge applications
Provide interfaces for
Video
Camera
Peripheral input (USB)
Combine FPGA and
GPU acceleration
Compact dimensions
1 RU, E-ATX form factor
(2 RU/ 3 RU for special cases)
RECS Architecture – t.RECS
Microserver #3
(COM-HPC Client)
Microserver #1
(COM-HPC Client)
Microserver #2
(COM-HPC Server)
Switched PCIe (Host to Host)
External
interfaces
PCIe
expansion
Ethernet (up to 10 GbE)
Management Network (KVM, Monitoring, …)
I/O (Camera, Display, Radar/Lidar, Audio)
9. 9
Peak performance values of specialized accelerators, provided by the vendors
(precisions varying from INT8 to FP32)
Peak Performance of DL Accelerators
Average efficiency at 1000 GOPS /W
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1
10
100
1,000
10,000
100,000
1,000,000
10,000,000
0.01 0.1 1 10 100 1000
Performance
[GOPS]
Power [Watt]
ASIC
GPU
FPGA
Ultra Low Power
High Performance
Low Power
10. 10
Yolo v4 accelerator performance
Performance of Yolo v4 for different hardware platform has been evaluated
Performance measurement for other networks (Resnet, EfficientNet) available as well
11. 11
Microserver Standardization – COM-HPC
• Large, open consortium
• Specification final and released
• Driven by industry requirements
12. 12
Microserver Standardization – COM-HPC
• Large, open consortium
• Specification final and released
• Driven by industry requirements
13. 13
▪ VEDLIoT accelerators support a large variety
of reconfigurable architectures
▪ From small embedded FPGAs to large ACAPs
▪ Large design space for FPGA-based accelerators
▪ Dynamic hardware reconfiguration
▪ Adapt to changing requirements at run-time
▪ Change characteristics of DL-accelerator
▪ Trade-off between
power and performance, power and accuracy, etc.
▪ Inference and training on FPGA
▪ Supports quantization from int8 to float32
▪ DL and Deep Reinforcement Learning
Reconfigurable DL accelerators
14. 14
DL accelerator co-design
"FiBHA: Fixed Budget Hybrid CNN Accelerator", Fareed Qararyah, Muhammad Waqar Azhar, Pedro Trancoso, IEEE 34th International Symposium on Computer Architecture and High-
Performance Computing (SBAC-PAD 2022), Bordeaux, France, November 2–5 2022
Monolithic design
● One engine computes
all the core layers
● E.g. TPU
SEML
● One engine computes all
layers of the same type
● PW engine, DW engine
SESL
● One engine per layer
● E.g. FINN
FiBHA
● SESL + SEML
15. 15
▪ Common environment for running distributed applications
▪ WebAssembly runtime + Trusted Execution Environment
▪ Security for edge (and cloud) devices
▪ Advances on attestation
▪ Better support for edge devices
▪ Distributed (Byzantine fault-tolerant) attestation and configuration service
▪ Secure IoT Gateway
Security
16. 16
Simulation platform for ML accelerators
▪ RISC-V SoCs and Custom Function Units
▪ Improve test and verification
▪ Co-simulate Verilog blocks
▪ Used in Google’s CFU Playground
▪ Continuous integration based in Gitlab and Google Cloud
Platform
Safety and Robustness
17. 17
A compositional architecture framework for AIoT
Knowledge creation (e.g.
definition of safety goals).
Concept design (e.g.
introduction of redundancy
to fulfil safety goals).
Final design (e.g. assigning
functions to independent
processors to guarantee
redundancy).
Monitoring concept definition
(e.g. monitoring fulfilment of
safety goals at run-time).
Solution
Space
Problem
Space
18. 18
▪ Focus on collision detection/avoidance scenario
▪ Improve performance/cost ratio – AI processing hardware
distributed over the entire chain
Use case: Automotive
Challenge:
Distribution
of work
19. 19
▪ Control applications need DL-based condition classification
▪ On the edge device for low power consumption
▪ Suggestions for control and maintenance
▪ DL methods on all communication layers
▪ DL in a distributed architecture
▪ Dynamically configured systems
▪ Sensored testbench with 2 motors
▪ Acceleration, Magnetic field, Temperature,
IR-Cam (temperature), Current-Sensors, Torque
Use case: Industrial IoT – drive condition classification
▪ On / Off detection without
motor current or voltage
▪ Cooling fault detection
▪ Bearing fault detection
Challenge:
Low-power /
Efficiency
20. 20
Use case: Industrial IoT – Arc detection
▪ AI based pattern recognition for different local sensor data
▪ current, magnetic field, vibration, temperature, low resolution infrared picture
▪ Safety critical nature
▪ response time should be <10ms
▪ AI based or AI supported decision made by the sensor node itself or by a local part of the sensor
network
Challenge:
Accuracy
21. 21
▪ Face recognition
▪ Mobilenet SSD trained on WIDERFACE dataset
▪ Object detection
▪ YoloV3, Efficient-Net, yoloV4-tiny
▪ Gesture detection
▪ YoloV4-tiny with 3 Yolo layers (usually: 2 layers)
▪ Speech recognition
▪ Mozilla DeepSpeech
▪ AI Art: Style-Gan trained on works of arts
▪ Collect usage data in situation memory
Use case: Smart Mirror – Neural Networks
Challenge:
Data privacy,
Efficiency
23. 23
Summary – Standardization in VEDLIoT
▪ Hardware/microserver form factors
▪ Active contribution to PICMG Standards COM-HPC and COM Express
(https://www.picmg.org/openstandards/com-hpc)
▪ Several Open Source contributions to large projects (https://vedliot.eu/open-source-software)
▪ Renode + Kenning – Emulator and Simulator for distributed IoT, Verilator support
▪ Memory Protection for RISC-V: RISC-V PMP
▪ TEEs support for WebAssembly: Integation for Trustzone (ARM) and SGX (Intel) into WebAssembly
▪ Recommendations: Design framework IoT and AI
▪ Compositional architecture framework for AIoT developled within VEDLIoT
▪ Can help system design to comply with regulatory constraints (e.g. EU AI Act)
24. 24
Thank you for your
attention.
Contact
Jens Hagemeyer, Carola Haumann
Bielefeld University, Germany
chaumann@cor-lab.uni-bielefeld.de
jhagemey@cit-ec.uni-bielefeld.de