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.
Dalghren, Thorne and Stebbins System of Classification of AngiospermsGurjant Singh
The Dahlgren, Thorne, and Stebbins system of classification is a modern method for categorizing angiosperms (flowering plants) based on phylogenetic relationships. Developed by botanists Rolf Dahlgren, Robert Thorne, and G. Ledyard Stebbins, this system emphasizes evolutionary relationships and incorporates extensive morphological and molecular data. It aims to provide a more accurate reflection of the genetic and evolutionary connections among angiosperm families and orders, facilitating a better understanding of plant diversity and evolution. This classification system is a valuable tool for botanists, researchers, and horticulturists in studying and organizing the vast diversity of flowering plants.
The X‐Pattern Merging of the Equatorial IonizationAnomaly Crests During Geoma...Sérgio Sacani
A unique phenomenon—A geomagnetically quiet time merging of Equatorial IonizationAnomaly (EIA) crests, leading to an X‐pattern (EIA‐X) around the magnetic equator—has been observed in thenight‐time ionospheric measurements by the Global‐scale Observations of the Limb and Disk mission. Thepattern is also reproduced in an ionospheric model that assimilates slant Total Electron Content from GlobalNavigation Satellite System and Constellation Observing System for Meteorology, Ionosphere, and Climate 2.A free‐running whole atmospheric general circulation model simulation reproduces a similar pattern. Due to thesimilarity between measurements and simulations, the latter is used to diagnose this heretofore unexplainedphenomenon. The simulation shows that the EIA‐X can occur during geomagnetically quiet conditions and inthe afternoon to evening sector at a longitude where the vertical drift is downward. The downward vertical driftis a necessary but not sufficient condition. The simulation was performed under constant low‐solar andquiescent‐geomagnetic forcing conditions, therefore we conclude that EIA‐X can be driven by lower‐atmospheric forcing.
CULEX MOSQUITOES, SYSTEMATIC CLASSIFICATION, MORPHOLOGY, LIFE CYCLE , CLINICA...DhakeshworShougrakpa
showing Culex mosquitoes' systematic classification, a completed life cycle i.e. egg, larva, pupa and adult mosquitoes also known as imago, also this slide showed the morphology of culex mosquitoes including head, thorax, abdomen, wing, egg larval stage, resting position,etc. by comparing with anopheles' mosquitoes. it's also showed the transmission of wuchereria bancrofti transmitted by vector Culex quinquefasciatus. Host: W. bancrofti completes its life cycle in
two hosts.
1. Definitive host: Man
2. Intermediate host: Mosquito named
Culex quinquefasciatus is the principle
vector worldwide. Rarely Anopheles
(rural Africa) or Aedes (Pacific Island)
can serve as a vector.
Infective form: Third stage filariform larvae
are the infective form found in the proboscis
of the mosquito.
Mode of transmission: L3
filariform larvae get
deposited in skin by the insect bite. Residents living in the endemic areas are exposed to
about 50–300 L3
larvae every year.Human cycle
z Develop into adults: Larvae penetrate
the skin, enter into lymphatic vessels and
migrate to the local lymph nodes where they
molt twice to develop into adult worms in
few months (4–6 weeks for B. malayi)
z Adults lay L1
larvae (microfilariae): Adult
worms reside in the afferent lymphatics or
cortical sinuses of the lymph nodes where
they mate and start laying the first stage
larvae (microfilariae). Male worms die after
mating where as the female worms live for
5–10 years. A gravid female can discharge
50,000 microfilariae/day
z Prepatent period: It is the time period
between the infection (entry of L3
larvae)
and diagnosis (detection of microfilariae
in blood). This is variable ranging from 80
days to 150 days
Mosquito cycle
z Transmission: When the mosquito bites
an infected man, the microfilariae are
ingested. Culex bites in night where as Aedes
bites in daytime
z Exsheathing: Microfilariae come out of the
sheath within 1–2 hours of ingestion
z Migration to thoracic muscle: L1
larvae
penetrate the stomach wall and migrate to
thoracic muscle in 6–12 hours where they
become sausage shaped (short and thick)
z Develop to infective L3
larvae: L1
larvae
molt twice to develop L2
(long and thick
form) followed by L3
(long and thin form).
The highly active L3
larvae migrate to the
labella (distal part of proboscis) of the
mosquito and serve as the infective stage
to man
z Extrinsic incubation period: Under
optimum conditions, the mosquito cycle
takes around 10–14 days
Clinical symptoms:
The clinical symptoms and signs are mainly determined by the duration of the infection. The
adult worms, which live in the lymphatic vessels, can cause severe inflammation of the
lymphatic system and acute recurrent fever. Secondary bacterial infections are a major factor in
the progression towards lymphoedema and elephantiasis, the characteristic swelling of the limbs,
genitalia and breasts.
treatment like using larvicide like fenthion can spray on water
ALTERNATIVE ANIMAL TOXICITY STUDY .pptxSAMIR PANDA
Alternatives animal testing are development and implementation of test methods that avoid the use of live animals.
Human biochemistry, physiology, pharmacology, and endocrinology and toxicology has been derived from animal models.10-100 millions of animals are using for experimentation in a year.
Animals used experimentation distributed among zebra- fish to primates.
Vast majority of animals are sacrificed at end of research programme.The use of animals can be further subdivided according to the degree of suffering
Minor animal suffering:- observing animals in behavioral studies, single blood sampling, Immunization without adjutants, etc.
Moderate animal suffering:- repeated blood sampling, recovery from general anesthesia, etc.
TOPIC: INTRODUCTION TO FORENSIC SCIENCE.pptximansiipandeyy
This presentation, "Introduction to Forensic Science," offers a basic understanding of forensic science, including its history, why it's needed, and its main goals. It covers how forensic science helps solve crimes and its importance in the justice system. By the end, you'll have a clear idea of what forensic science is and why it's essential.
The extremotolerant desert moss Syntrichia caninervis is a promising pioneer ...Sérgio Sacani
Many plans to establish human settlements on other planets focus on
adapting crops to growth in controlled environments. However, these settlements will also require pioneer plants that can grow in the soils and
harsh conditions found in extraterrestrial environments, such as those
on Mars. Here, we report the extraordinary environmental resilience of Syntrichia caninervis, a desert moss that thrives in various extreme environments. S. caninervis has remarkable desiccation tolerance; even after
losing >98% of its cellular water content, it can recover photosynthetic
and physiological activities within seconds after rehydration. Intact plants
can tolerate ultra-low temperatures and regenerate even after being stored
in a freezer at 80C for 5 years or in liquid nitrogen for 1 month.
S. caninervis also has super-resistance to gamma irradiation and can survive and maintain vitality in simulated Mars conditions; i.e., when simultaneously exposed to an anoxic atmosphere, extreme desiccation, low temperatures, and intense UV radiation. Our study shows that S. caninervis is
among the most stress tolerant organisms. This work provides fundamental insights into the multi-stress tolerance of the desert moss
S. caninervis, a promising candidate pioneer plant for colonizing extraterrestrial environments, laying the foundation for building biologically sustainable human habitats beyond Earth.
This an presentation about electrostatic force. This topic is from class 8 Force and Pressure lesson from ncert . I think this might be helpful for you. In this presentation there are 4 content they are Introduction, types, examples and demonstration. The demonstration should be done by yourself
This an presentation about electrostatic force. This topic is from class 8 Force and Pressure lesson from ncert . I think this might be helpful for you. In this presentation there are 4 content they are Introduction, types, examples and demonstration. The demonstration should be done by yourself
PART 1 The New Natural Principles of Electromagnetism and Electromagnetic Fie...Thane Heins
Document Summary and the History of Perpetual Motion
Every single Faraday Generator coil since 1834 has been and is currently performing Negative Work at infinite efficiency with created Electromagnetic Field Energy during electricity generation and its physical Kinetic Energy reduction or Electromagnetic Resistance of the changing magnetic field which is initially inducing Electric Current in the generator coil according to Faraday's Law of Induction.
The Work-Energy Principle confirms mathematically that the magnitude of the changing magnetic field's Kinetic Energy reduction is equal to the magnitude of Negative Work performed at infinite efficiency, which is equal to the magnitude of Energy (Electromagnetic Field Energy which is created according to Oersted's Law of Creation of Energy of 1820). Created Electromagnetic Field Energy is required in order to perform the Negative Work – because Work cannot be performed in the absence of Energy.
In 2007 Thane Heins of Almonte Ontario, Canada discovered that unlimited amounts of Positive Electromechanical Work could be performed at infinite efficiency with created and TIME DELAYED Electromagnetic Field Energy.
Every single ReGenX Generator coil since 2007 has been and is currently performing Positive Work at infinite efficiency with created Electromagnetic Field Energy during electricity generation and during its physical Kinetic Energy increase or Electromagnetic Assistance of the changing magnetic field which is initially inducing Electric Current in the generator coil according to Heins' Law of Induction.
Faraday Electric Generators all harness internally Created Electromagnetic Field Energy in order to perform Negative Work (system Kinetic Energy reduction) at infinite efficiency and ReGenX Electric Generators harness internally created and Time Delayed Electromagnetic Field Energy in order to perform Positive Work (system Kinetic Energy increase) at infinite efficiency.
Both Faraday Generators and ReGenX Generators operate as Perpetual Motion Machines of the First Kind because they both have the ability to perform both Negative or Positive Work indefinitely and at infinite efficiency without requiring any External Energy input. The unlimited Energy required to perform either the Negative or Positive Work is created at the Sub-Atomic Quantum Electron level inside the generators' Current Bearing Wires according to the Law of Creation of Energy.
Hans Christian Oersted discovered the Law of Creation of Energy in 1820 when he demonstrated the world's first Perpetual Motion Machine of the First Kind at the University of Copenhagen when he also simultaneously violated Newton's 1st, 2nd and 3rd Laws of Motion.
Michael Faraday built and demonstrated the world's second Perpetual Motion Machine of the First Kind in 1822 when he demonstrated his Electric Motor invention which harnessed created Electromagnetic Field Energy in order to perform Positive Electromechanical Work at infinite efficienc
Science-9-Lesson-1 ang lesson 2-NLC-pptx.pptxJoanaBanasen1
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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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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