This document provides a summary of a presentation about quantized neural network inference on FPGAs using FINN and LogicNets. It discusses:
- Xilinx Research Labs in Dublin and their work quantifying machine learning applications on Xilinx devices.
- How neural network quantization can improve efficiency by reducing precision while trading off accuracy, and how this is well-suited for FPGAs.
- The FINN toolflow which includes quantization-aware training in PyTorch with Brevitas, the FINN compiler to map networks to hardware, and deployment with PYNQ.
- LogicNets which further improves efficiency by unfolding DNNs into fully pipelined datapath circuits for
FreeRTOS basics (Real time Operating System)Naren Chandra
A presentation that covers all the basics needed to understand and start working with FreeRTOS . FreeRTOS is comparable with more than 20 controller families and 30 plus supporting tools and IDEs.
FreeRTOS is a market-leading real-time operating system (RTOS) for microcontrollers and small microprocessors. Distributed freely under the MIT open source license, FreeRTOS includes a kernel and a growing set of libraries suitable for use across all industry sectors. FreeRTOS is built with an emphasis on reliability and ease of use.
Tiny, power-saving kernel
Scalable size, with usable program memory footprint as low as 9KB. Some architectures include a tick-less power saving mode
Support for 40+ architectures
One code base for 40+ MCU architectures and 15+ toolchains, including the latest RISC-V and ARMv8-M (Arm Cortex-M33) microcontrollers
Modular libraries
A growing number of add-on libraries used across all industries sectors, including secure local or cloud connectivity
IoT Reference Integrations
Take advantage of tested examples that include all the libraries essential to securely connect to the cloud
In this deck, Yuichiro Ajima from Fujitsu presents: The Tofu Interconnect D.
"Through the development of post-K, which will be equipped with this CPU, Fujitsu will contribute to the resolution of social and scientific issues in such computer simulation fields as cutting-edge research, health and longevity, disaster prevention and mitigation, energy, as well as manufacturing, while enhancing industrial competitiveness and contributing to the creation of Society 5.0 by promoting applications in big data and AI fields."
Learn more: https://insidehpc.com/2018/08/fujitsu-unveils-details-post-k-supercomputer-processor-powered-arm/
and
http://www.fujitsu.com/jp/solutions/business-technology/tc/catalog/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
FreeRTOS basics (Real time Operating System)Naren Chandra
A presentation that covers all the basics needed to understand and start working with FreeRTOS . FreeRTOS is comparable with more than 20 controller families and 30 plus supporting tools and IDEs.
FreeRTOS is a market-leading real-time operating system (RTOS) for microcontrollers and small microprocessors. Distributed freely under the MIT open source license, FreeRTOS includes a kernel and a growing set of libraries suitable for use across all industry sectors. FreeRTOS is built with an emphasis on reliability and ease of use.
Tiny, power-saving kernel
Scalable size, with usable program memory footprint as low as 9KB. Some architectures include a tick-less power saving mode
Support for 40+ architectures
One code base for 40+ MCU architectures and 15+ toolchains, including the latest RISC-V and ARMv8-M (Arm Cortex-M33) microcontrollers
Modular libraries
A growing number of add-on libraries used across all industries sectors, including secure local or cloud connectivity
IoT Reference Integrations
Take advantage of tested examples that include all the libraries essential to securely connect to the cloud
In this deck, Yuichiro Ajima from Fujitsu presents: The Tofu Interconnect D.
"Through the development of post-K, which will be equipped with this CPU, Fujitsu will contribute to the resolution of social and scientific issues in such computer simulation fields as cutting-edge research, health and longevity, disaster prevention and mitigation, energy, as well as manufacturing, while enhancing industrial competitiveness and contributing to the creation of Society 5.0 by promoting applications in big data and AI fields."
Learn more: https://insidehpc.com/2018/08/fujitsu-unveils-details-post-k-supercomputer-processor-powered-arm/
and
http://www.fujitsu.com/jp/solutions/business-technology/tc/catalog/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/xilinx/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Nick Ni, Director of Product Marketing at Xilinx, presents the "Xilinx AI Engine: High Performance with Future-proof Architecture Adaptability" tutorial at the May 2019 Embedded Vision Summit.
AI inference demands orders- of-magnitude more compute capacity than what today’s SoCs offer. At the same time, neural network topologies are changing too quickly to be addressed by ASICs that take years to go from architecture to production. In this talk, Ni introduces the Xilinx AI Engine, which complements the dynamically- programmable FPGA fabric to enable ASIC-like performance via custom data flows and a flexible memory hierarchy. This combination provides an orders-of-magnitude boost in AI performance along with the hardware architecture flexibility needed to quickly adapt to rapidly evolving neural network topologies.
Low-cost microcontrollers are being used more and more often in embedded applications that previously may have used a microprocessor. Microcontrollers often run a real-time operating system (RTOS) rather than a full operating system like Linux. In this webinar we introduce FreeRTOS, a popular RTOS for microcontrollers that has been ported to 35 microcontroller platforms.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2022/06/tensorflow-lite-for-microcontrollers-tflm-recent-developments-a-presentation-from-bdti-and-google/
David Davis, Senior Embedded Software Engineer, and John Withers, Automation and Systems Engineer, both of BDTI, present the “TensorFlow Lite for Microcontrollers (TFLM): Recent Developments” tutorial at the May 2022 Embedded Vision Summit.
TensorFlow Lite Micro (TFLM) is a generic inference framework designed to run TensorFlow models on digital signal processors (DSPs), microcontrollers and other embedded targets with small memory footprints and very low power usage. TFLM aims to be easily portable to various embedded targets from those running an RTOS to bare-metal code. TFLM leverages the model optimization tools from the TensorFlow ecosystem and has additional embedded-specific optimizations to reduce the memory footprint. TFLM also integrates with a number of community contributed optimized hardware-specific kernel implementations.
In this talk, Davis and Withers review collaboration between BDTI and Google over the last year, including porting nearly two dozen operators from TensorFlow Lite to TFLM, creation of a separate Arduino examples repository, improved testing and documentation of both Arduino and Colab training examples and transitioning TFLM’s open-source CI framework to use GitHub Actions.
Enabling new protocol processing with DPDK using Dynamic Device PersonalizationMichelle Holley
Abstract: Dynamic Device Personalization allows a DPDK application to enable identification of new protocols, for example, GTP, PPPoE, QUIC, without changing the hardware. The demo showcases a DPDK application identifying and spreading traffic on GTP and QUIC. Dynamic Device Personalization can be used on any OS supported by DPDK, for example we showcase a QUIC protocol classification demo on Windows OS.
Speaker Bio: Brian Johnson is a Solutions Architect for Intel Ethernet products focusing on network packet processing, virtualization and NFV technologies. He is responsible for the definition and development of networking best practices for cloud and NFVi deployment technologies. Brian jhas over 20 years of experience in server and network product planning during which he held various positions in strategic planning, technical product marketing, and product development.
Prior to joining Intel in 1999, Brian held various technical and marketing roles for computer VARs and was the IT Administrator at the Daily Journal of Commerce in Portland, Oregon. He also served as the Vice Chair for the CompTIA Server+ and council member for CompTIA+ industry certifications.
Brian holds Bachelor of Science degree from Portland State University. Additionally, he has various technology certifications, CompTIA – A+, Server+, and Network+ and am FKA Certified Master Trainer.
In a series of announcements that left more than 1,200 gamers gathered in Cologne alternately breathless, giddy with laughter, and shouting their enthusiasm, Jensen Huang introduced the GeForce RTX series of gaming processors, representing the biggest leap in performance in NVIDIA’s history.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/altera/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Bill Jenkins, Senior Product Specialist for High Level Design Tools at Intel, presents the "Accelerating Deep Learning Using Altera FPGAs" tutorial at the May 2016 Embedded Vision Summit.
While large strides have recently been made in the development of high-performance systems for neural networks based on multi-core technology, significant challenges in power, cost and, performance scaling remain. Field-programmable gate arrays (FPGAs) are a natural choice for implementing neural networks because they can combine computing, logic, and memory resources in a single device. Intel's Programmable Solutions Group has developed a scalable convolutional neural network reference design for deep learning systems using the OpenCL programming language built with our SDK for OpenCL. The design performance is being benchmarked using several popular CNN benchmarks: CIFAR-10, ImageNet and KITTI.
Building the CNN with OpenCL kernels allows true scaling of the design from smaller to larger devices and from one device generation to the next. New designs can be sized using different numbers of kernels at each layer. Performance scaling from one generation to the next also benefits from architectural advancements, such as floating-point engines and frequency scaling. Thus, you achieve greater than linear performance and performance per watt scaling with each new series of devices.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/06/accelerating-newer-ml-models-using-the-qualcomm-ai-stack-a-presentation-from-qualcomm/
Vinesh Sukumar, Senior Director and Head of AI/ML Product Management at Qualcomm Technologies, presents the “Accelerating Newer ML Models Using the Qualcomm AI Stack” tutorial at the May 2023 Embedded Vision Summit.
The Qualcomm AI Stack revolutionizes how Qualcomm thinks about AI software and provides the ultimate tool and user interface to enable ecosystem partners to create faster and smarter AI applications for all embedded form factors. Focusing on real user experience challenges centered around model deployment, Sakumar explains how the Snapdragon developer community leverages data types, quantization and neural architecture search—among others—to optimize complex AI architectures for emerging use cases.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/xilinx/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Nick Ni, Director of Product Marketing at Xilinx, presents the "Xilinx AI Engine: High Performance with Future-proof Architecture Adaptability" tutorial at the May 2019 Embedded Vision Summit.
AI inference demands orders- of-magnitude more compute capacity than what today’s SoCs offer. At the same time, neural network topologies are changing too quickly to be addressed by ASICs that take years to go from architecture to production. In this talk, Ni introduces the Xilinx AI Engine, which complements the dynamically- programmable FPGA fabric to enable ASIC-like performance via custom data flows and a flexible memory hierarchy. This combination provides an orders-of-magnitude boost in AI performance along with the hardware architecture flexibility needed to quickly adapt to rapidly evolving neural network topologies.
Low-cost microcontrollers are being used more and more often in embedded applications that previously may have used a microprocessor. Microcontrollers often run a real-time operating system (RTOS) rather than a full operating system like Linux. In this webinar we introduce FreeRTOS, a popular RTOS for microcontrollers that has been ported to 35 microcontroller platforms.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2022/06/tensorflow-lite-for-microcontrollers-tflm-recent-developments-a-presentation-from-bdti-and-google/
David Davis, Senior Embedded Software Engineer, and John Withers, Automation and Systems Engineer, both of BDTI, present the “TensorFlow Lite for Microcontrollers (TFLM): Recent Developments” tutorial at the May 2022 Embedded Vision Summit.
TensorFlow Lite Micro (TFLM) is a generic inference framework designed to run TensorFlow models on digital signal processors (DSPs), microcontrollers and other embedded targets with small memory footprints and very low power usage. TFLM aims to be easily portable to various embedded targets from those running an RTOS to bare-metal code. TFLM leverages the model optimization tools from the TensorFlow ecosystem and has additional embedded-specific optimizations to reduce the memory footprint. TFLM also integrates with a number of community contributed optimized hardware-specific kernel implementations.
In this talk, Davis and Withers review collaboration between BDTI and Google over the last year, including porting nearly two dozen operators from TensorFlow Lite to TFLM, creation of a separate Arduino examples repository, improved testing and documentation of both Arduino and Colab training examples and transitioning TFLM’s open-source CI framework to use GitHub Actions.
Enabling new protocol processing with DPDK using Dynamic Device PersonalizationMichelle Holley
Abstract: Dynamic Device Personalization allows a DPDK application to enable identification of new protocols, for example, GTP, PPPoE, QUIC, without changing the hardware. The demo showcases a DPDK application identifying and spreading traffic on GTP and QUIC. Dynamic Device Personalization can be used on any OS supported by DPDK, for example we showcase a QUIC protocol classification demo on Windows OS.
Speaker Bio: Brian Johnson is a Solutions Architect for Intel Ethernet products focusing on network packet processing, virtualization and NFV technologies. He is responsible for the definition and development of networking best practices for cloud and NFVi deployment technologies. Brian jhas over 20 years of experience in server and network product planning during which he held various positions in strategic planning, technical product marketing, and product development.
Prior to joining Intel in 1999, Brian held various technical and marketing roles for computer VARs and was the IT Administrator at the Daily Journal of Commerce in Portland, Oregon. He also served as the Vice Chair for the CompTIA Server+ and council member for CompTIA+ industry certifications.
Brian holds Bachelor of Science degree from Portland State University. Additionally, he has various technology certifications, CompTIA – A+, Server+, and Network+ and am FKA Certified Master Trainer.
In a series of announcements that left more than 1,200 gamers gathered in Cologne alternately breathless, giddy with laughter, and shouting their enthusiasm, Jensen Huang introduced the GeForce RTX series of gaming processors, representing the biggest leap in performance in NVIDIA’s history.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/altera/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Bill Jenkins, Senior Product Specialist for High Level Design Tools at Intel, presents the "Accelerating Deep Learning Using Altera FPGAs" tutorial at the May 2016 Embedded Vision Summit.
While large strides have recently been made in the development of high-performance systems for neural networks based on multi-core technology, significant challenges in power, cost and, performance scaling remain. Field-programmable gate arrays (FPGAs) are a natural choice for implementing neural networks because they can combine computing, logic, and memory resources in a single device. Intel's Programmable Solutions Group has developed a scalable convolutional neural network reference design for deep learning systems using the OpenCL programming language built with our SDK for OpenCL. The design performance is being benchmarked using several popular CNN benchmarks: CIFAR-10, ImageNet and KITTI.
Building the CNN with OpenCL kernels allows true scaling of the design from smaller to larger devices and from one device generation to the next. New designs can be sized using different numbers of kernels at each layer. Performance scaling from one generation to the next also benefits from architectural advancements, such as floating-point engines and frequency scaling. Thus, you achieve greater than linear performance and performance per watt scaling with each new series of devices.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2023/06/accelerating-newer-ml-models-using-the-qualcomm-ai-stack-a-presentation-from-qualcomm/
Vinesh Sukumar, Senior Director and Head of AI/ML Product Management at Qualcomm Technologies, presents the “Accelerating Newer ML Models Using the Qualcomm AI Stack” tutorial at the May 2023 Embedded Vision Summit.
The Qualcomm AI Stack revolutionizes how Qualcomm thinks about AI software and provides the ultimate tool and user interface to enable ecosystem partners to create faster and smarter AI applications for all embedded form factors. Focusing on real user experience challenges centered around model deployment, Sakumar explains how the Snapdragon developer community leverages data types, quantization and neural architecture search—among others—to optimize complex AI architectures for emerging use cases.
DPDK Summit 2015 - NTT - Yoshihiro NakajimaJim St. Leger
DPDK Summit 2015 in San Francisco.
NTT presentation by Yoshihiro Nakajima.
For additional details and the video recording please visit www.dpdksummit.com.
Hai Tao at AI Frontiers: Deep Learning For Embedded Vision SystemAI Frontiers
This presentation will demonstrate our recent progress in developing advanced computer vision algorithms using embedded platforms for video-based face recognition, vehicle attribute analysis, urban management event detection, and high-density crowd counting. These algorithms combine the traditional CV approach with recent advances in deep learning to make high-performance computer vision systems practical and enable products in several vertical markets including intelligent transportation systems (ITS), business intelligence (BI), and smart video surveillance. We will demonstrate algorithm design and optimization scheme for several recently available processors from Movidius, Nvidia, and ARM.
HKG18-300K2 - Keynote: Tomas Evensen - All Programmable SoCs? – Platforms to ...Linaro
Session ID: HKG18-300K2
Session Name: HKG18-300K2 - Keynote: Tomas Evensen - All Programmable SoCs? – Platforms to enable the future of Embedded Machine Learning
Speaker: Tomas Evensen
Track: Ecosystem Day
★ Session Summary ★
As Moore's law is slowing down, heterogeneous architectures are needed to keep up with the increasing compute requirements emerging from industry trends such as the use machine learning across a diverse range of markets and applications. These compute requirements require custom system architectures to suit the rapidly evolving demands of emerging algorithms, standards and trends.
Field Programmable hardware offers a unique capability to provide flexibility alongside advanced processor architectures to address this ever increasing multitude of applications. Development flows, programmability and flexibility are crucial to the enablement of these advancing algorithms and to enable the next generation of implementations in a world of advancing Artificial intelligence.
In this session we will introduce you to an all Programmable paradigm and low cost development platform to enable an ecosystem of flexibility and unparalleled programmability.
The future is now…...
---------------------------------------------------
★ Resources ★
Event Page: http://connect.linaro.org/resource/hkg18/hkg18-300k2/
Presentation: http://connect.linaro.org.s3.amazonaws.com/hkg18/presentations/hkg18-300k2.pdf
Video: http://connect.linaro.org.s3.amazonaws.com/hkg18/videos/hkg18-300k2.mp4
---------------------------------------------------
★ Event Details ★
Linaro Connect Hong Kong 2018 (HKG18)
19-23 March 2018
Regal Airport Hotel Hong Kong
---------------------------------------------------
Keyword: Ecosystem Day
'http://www.linaro.org'
'http://connect.linaro.org'
---------------------------------------------------
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Brain in the Cloud: Machine Learning on OpenStack & Kubernetes Done Right - E...Cloud Native Day Tel Aviv
Machine Learning is no doubt the hottest trend in IT nowadays. Deep Neural Network (DNN), a subfield of Machine Learning with mode of operation loosely inspired by the brain, allows us to solve complex problems such as image recognition that has been very difficult to solve using standard programming paradigms. DNN concepts are not new. However, and until recently, applying them in practice could not be realized due to their high computational demands. With the recent development in parallel computing, especially around GPU acceleration and high speed and efficient networking, DNN has become a reality in modern data centers. In this talk we will describe the system requirements to effectively run a machine learning cluster with popular frameworks such as TensorFlow. We will discuss how such a system can be deployed in an OpenStack-based cloud without compromises, enjoying high-performance DNN programming paradigm as well as the benefits of cloud and software-defined data centers.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/12/trends-in-neural-network-topologies-for-vision-at-the-edge-a-presentation-from-synopsys/
For more information about edge AI and computer vision, please visit:
https://www.edge-ai-vision.com
Pierre Paulin, Director of R&D for Embedded Vision at Synopsys, presents the “Trends in Neural Network Topologies for Vision at the Edge” tutorial at the September 2020 Embedded Vision Summit.
The widespread adoption of deep neural networks (DNNs) in embedded vision applications has increased the importance of creating DNN topologies that maximize accuracy while minimizing computation and memory requirements. This has led to accelerated innovation in DNN topologies.
In this talk, Paulin summarizes the key trends in neural network topologies for embedded vision applications, highlighting techniques employed by widely used networks such as EfficientNet and MobileNet to boost both accuracy and efficiency. He also touches on other optimization methods—such as pruning, compression and layer fusion—that developers can use to further reduce the memory and computation demands of modern DNNs.
DPDK Summit - 08 Sept 2014 - 6WIND - High Perf Networking Leveraging the DPDK...Jim St. Leger
Thomas Monjalon, 6WIND, presents on where/how to use DPDK, the DPDK ecosystem, and the DPDK.org community.
Thomas is the community maintainer of DPDK.org.
6WIND - SPEED MATTERS: The Challenge 2014 Contest Winners6WIND
Winners of SPEED MATTERS: The Challenge, DPDK Contest announced on August 26, 2014 at Google headquarters in Mountain View, California during Hot Interconnects (HOTI).
Hands-On Workshop on Performance Optimization for Intel Xeon Phi Processor Family x200 (formerly Knights Landing) from Colfax International. More information at http://colfaxresearch.com/knl-webinar/
Kirill Tsym discusses Vector Packet Processing:
* Linux Kernel data path (in short), initial design, today's situation, optimization initiatives
* Brief overview of DPDK, Netmap, etc.
* Userspace Networking projects comparison: OpenFastPath, OpenSwitch, VPP.
* Introduction to VPP: architecture, capabilities and optimization techniques.
* Basic Data Flow and introduction to vectors.
* VPP Single and Multi-thread modes.
* Router and switch for namespaces example.
* VPP L4 protocol processing - Transport Layer Development Kit.
* VPP Plugins.
Kiril is a software developer at Check Point Software Technologies, part of Next Generation Gateway and Architecture team, developing proof of concept around DPDK and FD.IO VPP. He has years of experience in software, Linux kernel and networking development and has worked for Polycom, Broadcom and Qualcomm before joining Check Point.
Netronome invented the flexible network flow processor and hardware-accelerated server-based networking. Learn more from Netronome's Corporate Brochure.
Competition Briefing - Open Digital Solutions for Net Zero Energy KTN
This briefing provided more information on the scope and application process for Innovate UK's Small Business Research Initiative (SBRI) competition to develop open software, hardware and data solutions that address the challenges of transforming to a net zero energy system in the UK.
An Introduction to Eurostars - an Opportunity for SMEs to Collaborate Interna...KTN
This webinar highlighted opportunities within the EUREKA Eurostars programme and how Innovate UK KTN and partners can help your business to innovate and go international.
Prospering from the Energy Revolution: Six in Sixty - Technology and Infrastr...KTN
Hear about one of the key facets of PFER, a £104m programme focussed on the integration of power, heat and transport and the business models needed to enable Smart Local Energy Systems (SLES) to scale towards net zero.
UK Catalysis: Innovation opportunities for an enabling technologyKTN
Read about how accelerating innovations in catalysis will play a vital role in enabling the UK to meet its net zero targets in the areas of hydrogen production, Power-to-X, carbon dioxide utilisation and the use of alternative feedstocks.
Industrial Energy Transformational Fund Phase 2 Spring 2022 - Competition Bri...KTN
The Phase 2 competition for England, Wales and Northern Ireland opens on the 31st January 2022 and runs until 29th April 2022 and is worth up to £60 million in funding.
Horizon Europe ‘Culture, Creativity and Inclusive Society’ Consortia Building...KTN
This webinar highlights relevant call topics within Cluster 2 which focuses on challenges pertaining to democratic governance, cultural heritage and the creative economy, as well as social and economic transformations.
Horizon Europe ‘Culture, Creativity and Inclusive Society’ Consortia Building...KTN
This webinar highlights relevant call topics within Cluster 2 which focuses on challenges pertaining to democratic governance, cultural heritage and the creative economy, as well as social and economic transformations.
Building Talent for the Future 2 – Expression of Interest BriefingKTN
This competition briefing is supporting the creation, delivery, and growth of PEMD industry-focused course content, materials, and support for skills plus training.
Performance Projects specialises in niche vehicle and motorsport innovation, designing, building and supplying complex subsystems through to whole vehicles.
How to Create a Good Horizon Europe Proposal WebinarKTN
This webinar provides you with the essential hands-on knowledge and skills to transform your innovative project ideas into competitive project proposals in response to calls under Horizon Europe.
Horizon Europe Tackling Diseases and Antimicrobial Resistance (AMR) Webinar a...KTN
Innovate UK KTN Global Alliance in partnership with the Foreign, Commonwealth and Development Office (FCDO) the UK Science and Innovation Network in Ireland and the Nordics, and UK National Contact Points (NCPs) from Innovate UK (UKRI) hosted a workshop to help delegates form international collaborations and strategic partnerships.
Custom Interconnect Ltd (CIL) is a global provider of engineering solutions for mission critical applications. Based in Andover it has the most advanced electronic assembly facility in the UK, ranging from 6 SMT lines, 3D AOI, flying probe test, X-Ray/CT-Scan, laser depanelling, vacuum assisted vapour phase, 7 auto wire-bonders and 3 auto die bonders, and a scanning acoustic microscope.
ZF is a global technology company that supplies systems for passenger cars, commercial vehicles and industrial technology, enabling the next generation of mobility. ZF allows vehicles to see, think and act. In the four technology domains Vehicle Motion Control, Integrated Safety, Automated Driving, and Electric Mobility, ZF offers comprehensive solutions for established vehicle manufacturers and newly emerging transport and mobility service providers.
FluxSys was formed in 2013, from their base in Wellesbourne, Warwickshire they support their UK and international clients with the specification, design and prototyping of a wide range of electric machines and drives.
FluxSys uses its skills, experience and independence within customers’ projects to support their electrification journeys and skills development, utilising knowledge sharing in an open & collaborative manner with like-minded clients and technical experts.
Made Smarter Innovation: Sustainable Smart Factory Competition BriefingKTN
This competition briefing outlines how this funding opportunity aims to support industrial research that addresses digital innovations to improve the sustainability of manufacturing processes.
Driving the Electric Revolution – PEMD Skills HubKTN
Watch this briefing webinar to find out more about this new competition which supports the development of the Skills Hub, a training platform to support the PEMD sector.
Medicines Manufacturing Challenge EDI Survey Briefing WebinarKTN
In anticipation of the Medicines Manufacturing Challenge sending out an EDI survey to those involved in any projects funded under the programme, this webinar provides more context behind the request, an overview of the Innovate UK Equality, Diversity and Inclusion (EDI) programmes, and an opportunity for attendees to ask questions and get involved.
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
What are the main advantages of using HR recruiter services.pdfHumanResourceDimensi1
HR recruiter services offer top talents to companies according to their specific needs. They handle all recruitment tasks from job posting to onboarding and help companies concentrate on their business growth. With their expertise and years of experience, they streamline the hiring process and save time and resources for the company.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
Tata Group Dials Taiwan for Its Chipmaking Ambition in Gujarat’s DholeraAvirahi City Dholera
The Tata Group, a titan of Indian industry, is making waves with its advanced talks with Taiwanese chipmakers Powerchip Semiconductor Manufacturing Corporation (PSMC) and UMC Group. The goal? Establishing a cutting-edge semiconductor fabrication unit (fab) in Dholera, Gujarat. This isn’t just any project; it’s a potential game changer for India’s chipmaking aspirations and a boon for investors seeking promising residential projects in dholera sir.
Visit : https://www.avirahi.com/blog/tata-group-dials-taiwan-for-its-chipmaking-ambition-in-gujarats-dholera/
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[Note: This is a partial preview. To download this presentation, visit:
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Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
6. Benefits of Quantization on FPGAs
6
On-chip weights
~60 M
~30 M
~10 M
~5 M
~2 M
Precision
1b
4b
8b
16b
32b
Xilinx UltraScale+ MPSoC ZU19EG (Vivado HLS, conservative estimates)
30x
Approx. Peak GOPS
66 000
20 000
4 000
1 000
300
200x
Trillions of quantized
operations per
second
Weights can
stay entirely
on-chip
compute memory
Great for energy efficiency! But what about accuracy?
14. 14
QNN training in PyTorch
Brevitas
Frontends, Transformation,
Dataflow Backend
FINN Compiler
Deployment with
Quantization-Aware
Training in PyTorch
with Brevitas
16. The FINN Compiler
16
QNN training in PyTorch
Brevitas
Frontends, Transformation,
Dataflow Backend
FINN Compiler
Deployment with
17. An Overview of the FINN Compiler
17
› Python library of graph transformations
» Each consumes and produces an ONNX graph
› User calls sequence of transformations to
create their own flow
» Example end-to-end flows to get started
Code Generator
Import
FINN HLS Library
Synthesizable
description
Hardware Cost Model
Vivado
Synthesis, PAR
Software Library
Host Run-time FPGA Platform
ONNX
Streamlining
Hardware Mapping
Resource Allocation
https://github.com/Xilinx/finn
18. Deployment with PYNQ
18
QNN training in PyTorch
Brevitas
Frontends, Transformation,
Dataflow Backend
FINN Compiler
Deployment with
19. Deployment with for Python Productivity
19
› Use PYNQ-provided Python abstractions and drivers
› User provides Numpy array in, calls driver, gets Numpy array out
» Internally use PYNQ DMA driver to wr/rd NumPy arrays into I/O streams
# numpy array shapes for i/o
ishape_packed = (1, 49, 2)
oshape_packed = (1, 1, 40)
# set up the DMA
dma.sendchannel.transfer(ibuf_packed_device)
dma.recvchannel.transfer(obuf_packed)
# wait until all transfers complete
dma.sendchannel.wait()
dma.recvchannel.wait()
https://github.com/Xilinx/PYNQ