Presented at NAFEMS DACH regional conference for numerical simulation methods by LCM and cloudSME in Wiesbaden on the 14th of November 2019.
The Linz Center of Mechatronics GmbH showcased how they easily optimize electrical drive engines in the cloud.
We supported LCM to work out the right cloud-based service solutions for their customers based on their existing software. By respecting the latest developments in the industry and science, including security and privacy compliance and hosting flexibility (free choice of data centre, no vendor lock-in).
Check out their cool System Model Space "SyMSpace" for electrical drive engines and trusted by industrial partners! (https://bit.ly/2CKGphb) #poweredbycloudSME
Yes, Cloud Computing is offering a broad range of actions and can be confusing. You want to dig deeper?
Write us an email or give us a call so that we can work out how to approach the perfect cloud solution for your needs.
Enabling Machine Learning on the Edge using SRAM Conserving Efficient Neural ...Bharath Sudharsan
Paper Pdf: https://scholarcommons.sc.edu/aii_fac_pub/520/
Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the device level, enabling autonomous decision-making, without depending on the cloud. However, the majority of Internet of Things (IoT) devices are embedded systems with a low-cost microcontroller unit (MCU) or a small CPU as its brain, which often are incapable of handling complex ML algorithms.
In this paper, we propose an approach for the efficient execution of already deeply compressed, large neural networks (NNs) on tiny IoT devices. After optimizing NNs using state-of-the-art deep model compression methods, when the resultant models are executed by MCUs or small CPUs using the model execution sequence produced by our approach, higher levels of conserved SRAM can be achieved. During the evaluation for nine popular models, when comparing the default NN execution sequence with the sequence produced by our approach, we found that 1.61-38.06\% less SRAM was used to produce inference results, the inference time was reduced by 0.28-4.9 ms, and energy consumption was reduced by 4-84 mJ. Despite achieving such high conserved levels of SRAM, our method 100% preserved the accuracy, F1 score, etc. (model performance).
[Capella Day 2019] Model execution and system simulation in CapellaObeo
A common need in system architecture design is to verify that if the architect is correct and can satisfy its requirements. Execution of system architect model means to interact with state machines to test system’s control logic. It can verify if the logical sequences of functions and interfaces in different scenarios are desired.
However, only sequence itself is not enough to verify its consequence or output. So we need each function to do what it is supposed to do during model execution to verify its output, and that is what we called “system simulation”.
This presentation introduces how we do model execution in Capella, and how to embed digital mockup inside functions to do “system simulation” with a higher confidence.
Renfei Xu, Glaway
Renfei Xu is the technical manager of MBSE solution in Glaway. He has participated in many pilot projects of MBSE in areas like Engine Control, Avionics, Mechatronics and so on. In recent years, he is responsible for the deployment of MBSE using Capella and ARCADIA methodology in a Radar research institute.
Wenhua Fang, Glaway
Wenhua Fang is the Director of Systems Engineering in Glaway. He has more than 12 years of working experience in SE.
He is responsible for more than 10 implementation projects of MBSE in areas like Aircraft, Engine Control, Avionics, Automotive and so on. In recent years, he leads the team to deploy MBSE in China(including using Capella and ARCADIA methodology).
Nafems15 Technical meeting on system modelingSDTools
This presentation illustrates the main mechanisms of model reduction used in generating efficient system models that can be used in vibration design. Examples from automotive, aeronautics and train industries are used as illustrations.
Dr. Konstantinos Giannoutakis presents the CloudLightning simulator, a bespoke cloud simulation engine built for modelling and simulating heterogeneous resources as well as self-organising systems.
This presentation was given at the CloudLightning Conference held in conjunction with NC4 2017 in Dublin City University on 11th April 2017.
Low cost high-performance vlsi architecture for montgomery modular multiplica...LogicMindtech Nologies
VLSI Projects for M. Tech, VLSI Projects in Vijayanagar, VLSI Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, VLSI IEEE projects in Bangalore, IEEE 2015 VLSI Projects, FPGA and Xilinx Projects, FPGA and Xilinx Projects in Bangalore, FPGA and Xilinx Projects in Vijayangar
Enabling Machine Learning on the Edge using SRAM Conserving Efficient Neural ...Bharath Sudharsan
Paper Pdf: https://scholarcommons.sc.edu/aii_fac_pub/520/
Edge analytics refers to the application of data analytics and Machine Learning (ML) algorithms on IoT devices. The concept of edge analytics is gaining popularity due to its ability to perform AI-based analytics at the device level, enabling autonomous decision-making, without depending on the cloud. However, the majority of Internet of Things (IoT) devices are embedded systems with a low-cost microcontroller unit (MCU) or a small CPU as its brain, which often are incapable of handling complex ML algorithms.
In this paper, we propose an approach for the efficient execution of already deeply compressed, large neural networks (NNs) on tiny IoT devices. After optimizing NNs using state-of-the-art deep model compression methods, when the resultant models are executed by MCUs or small CPUs using the model execution sequence produced by our approach, higher levels of conserved SRAM can be achieved. During the evaluation for nine popular models, when comparing the default NN execution sequence with the sequence produced by our approach, we found that 1.61-38.06\% less SRAM was used to produce inference results, the inference time was reduced by 0.28-4.9 ms, and energy consumption was reduced by 4-84 mJ. Despite achieving such high conserved levels of SRAM, our method 100% preserved the accuracy, F1 score, etc. (model performance).
[Capella Day 2019] Model execution and system simulation in CapellaObeo
A common need in system architecture design is to verify that if the architect is correct and can satisfy its requirements. Execution of system architect model means to interact with state machines to test system’s control logic. It can verify if the logical sequences of functions and interfaces in different scenarios are desired.
However, only sequence itself is not enough to verify its consequence or output. So we need each function to do what it is supposed to do during model execution to verify its output, and that is what we called “system simulation”.
This presentation introduces how we do model execution in Capella, and how to embed digital mockup inside functions to do “system simulation” with a higher confidence.
Renfei Xu, Glaway
Renfei Xu is the technical manager of MBSE solution in Glaway. He has participated in many pilot projects of MBSE in areas like Engine Control, Avionics, Mechatronics and so on. In recent years, he is responsible for the deployment of MBSE using Capella and ARCADIA methodology in a Radar research institute.
Wenhua Fang, Glaway
Wenhua Fang is the Director of Systems Engineering in Glaway. He has more than 12 years of working experience in SE.
He is responsible for more than 10 implementation projects of MBSE in areas like Aircraft, Engine Control, Avionics, Automotive and so on. In recent years, he leads the team to deploy MBSE in China(including using Capella and ARCADIA methodology).
Nafems15 Technical meeting on system modelingSDTools
This presentation illustrates the main mechanisms of model reduction used in generating efficient system models that can be used in vibration design. Examples from automotive, aeronautics and train industries are used as illustrations.
Dr. Konstantinos Giannoutakis presents the CloudLightning simulator, a bespoke cloud simulation engine built for modelling and simulating heterogeneous resources as well as self-organising systems.
This presentation was given at the CloudLightning Conference held in conjunction with NC4 2017 in Dublin City University on 11th April 2017.
Low cost high-performance vlsi architecture for montgomery modular multiplica...LogicMindtech Nologies
VLSI Projects for M. Tech, VLSI Projects in Vijayanagar, VLSI Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, VLSI IEEE projects in Bangalore, IEEE 2015 VLSI Projects, FPGA and Xilinx Projects, FPGA and Xilinx Projects in Bangalore, FPGA and Xilinx Projects in Vijayangar
Design and Implementation of Low Power DSP Core with Programmable Truncated V...ijsrd.com
The programmable truncated Vedic multiplication is the method which uses Vedic multiplier and programmable truncation control bits and which reduces part of the area and power required by multipliers by only computing the most-significant bits of the product. The basic process of truncation includes physical reduction of the partial product matrix and a compensation for the reduced bits via different hardware compensation sub circuits. These results in fixed systems optimized for a given application at design time. A novel approach to truncation is proposed, where a full precision vedic multiplier is implemented, but the active section of the truncation is selected by truncation control bits dynamically at run-time. Such architecture brings together the power reduction benefits from truncated multipliers and the flexibility of reconfigurable and general purpose devices. Efficient implementation of such a multiplier is presented in a custom digital signal processor where the concept of software compensation is introduced and analyzed for different applications. Experimental results and power measurements are studied, including power measurements from both post-synthesis simulations and a fabricated IC implementation. This is the first system-level DSP core using a high speed Vedic truncated multiplier. Results demonstrate the effectiveness of the programmable truncated MAC (PTMAC) in achieving power reduction, with minimum impact on functionality for a number of applications. On comparison with the previous parallel multipliers Vedic should be much more fast and area should be reduced. Programmable truncated Vedic multiplier (PTVM) should be the basic part implemented for the arithmetic and PTMAC units.
Hardware Architecture for Calculating LBP-Based Image Region DescriptorsMarek Kraft
In this paper, an efficient hardware architecture, enabling the computation of LBP-based image region descriptors is presented. The complete region descriptor is formed by combining individual local descriptors and arranging them into a grid, as typically used in object detection and recognition. The proposed solution performs massively parallel, pipelined computations, facilitating the processing of over two hundred VGA frames per second and can easily be adopted to different window and grid sizes for the use of other descriptors.
Basic description about how to do a Space Project, based on experiences with XaTcobeo cubesat, a University of Vigo project for ESA education, with the help of INTA.
License: Breogan Costa, University of Vigo, CERN, JINR.
Microarchitecture of a coarse grain out-of-order superscalar processorecway
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects in Chennai, 2013 IEEE JAVA, .NET Projects in Trichy, 2013 IEEE JAVA, .NET Projects in Karur, 2013 IEEE JAVA, .NET Projects in Erode, 2013 IEEE JAVA, .NET Projects in Madurai, 2013 IEEE JAVA, .NET Projects in Salem, 2013 IEEE JAVA, .NET Projects in Coimbatore, 2013 IEEE JAVA, .NET Projects in Tirupur, 2013 IEEE JAVA, .NET Projects in Bangalore, 2013 IEEE JAVA, .NET Projects in Hydrabad, 2013 IEEE JAVA, .NET Projects in Kerala, 2013 IEEE JAVA, .NET Projects in Namakkal, IEEE JAVA, .NET Image Processing, IEEE JAVA, .NET Face Recognition, IEEE JAVA, .NET Face Detection, IEEE JAVA, .NET Brain Tumour, IEEE JAVA, .NET Iris Recognition, IEEE JAVA, .NET Image Segmentation, Final Year JAVA, .NET Projects in Pondichery, Final Year JAVA, .NET Projects in Tamilnadu, Final Year JAVA, .NET Projects in Chennai, Final Year JAVA, .NET Projects in Trichy, Final Year JAVA, .NET Projects in Erode, Final Year JAVA, .NET Projects in Karur, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Tirunelveli, Final Year JAVA, .NET Projects in Madurai, Final Year JAVA, .NET Projects in Salem, Final Year JAVA, .NET Projects in Tirupur, Final Year JAVA, .NET Projects in Namakkal, Final Year JAVA, .NET Projects in Tanjore, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Bangalore, Final Year JAVA, .NET Projects in Hydrabad, Final Year JAVA, .NET Projects in Kerala, Final Year JAVA, .NET IEEE Projects in Pondichery, Final Year JAVA, .NET IEEE Projects in Tamilnadu, Final Year JAVA, .NET IEEE Projects in Chennai, Final Year JAVA, .NET IEEE Projects in Trichy, Final Year JAVA, .NET IEEE Projects in Erode, Final Year JAVA, .NET IEEE Projects in Karur, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Tirunelveli, Final Year JAVA, .NET IEEE Projects in Madurai, Final Year JAVA, .NET IEEE Projects in Salem, Final Year JAVA, .NET IEEE Projects in Tirupur, Final Year JAVA, .NET IEEE Projects in Namakkal, Final Year JAVA, .NET IEEE Projects in Tanjore, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Bangalore, Final Year JAVA, .NET IEEE Projects in Hydrabad, Final Year JAVA, .NET IEEE Projects in Kerala, Final Year IEEE MATLAB Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE MATLAB Projects, Academic Final Year IEEE MATLAB Projects 2013, Academic Final Year IEEE MATLAB Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB
This Virtual User Group session, held on 2014-01-22, presents some of the techniques and algorithms used to improve the CPLEX MIP solver in versions 12.5.1 and 12.6.
Model Compression (NanheeKim)
@NanheeKim @nh9k
질문이 있으면 언제든지 연락주세요!
공부한 것을 바탕으로 작성한 ppt입니다.
출처는 슬라이드 마지막에 있습니다!
Please, feel free to contact me, if you have any questions!
github: https://github.com/nh9k
email: kimnanhee97@gmail.com
byteLAKE's expertise across NVIDIA architectures and configurationsbyteLAKE
AI Solutions for Industries | Quality Inspection | Data Insights | AI-accelerated CFD | Self-Checkout | byteLAKE.com
byteLAKE: Empowering Industries with AI Solutions. Embrace cutting-edge technology for advanced quality inspection, data insights, and more. Harness the potential of our CFD Suite, accelerating Computational Fluid Dynamics for heightened productivity. Unlock new possibilities with Cognitive Services: image analytics for precise visual inspection for Manufacturing, sound analytics enabling proactive maintenance for Automotive, and wet line analytics for the Paper Industry. Seamlessly convert data into actionable insights using Data Insights' AI module, enabling advanced predictive maintenance and risk detection. Simplify Restaurant and Retail operations with our efficient self-checkout solution, recognizing meals and groceries and elevating customer satisfaction. Custom AI Development services available for tailored solutions. Discover more at www.byteLAKE.com.
How to achieve 95%+ Accurate power measurement during architecture exploration? Deepak Shankar
During the conceptualization and architectural exploration phases, it is crucial to assess the power budget.
Would you like to accurately measure the:
1. Power consumed for a proposed embedded software or firmware?
2. Savings of a Power Management Algorithm prior to development?
3. Power impact of hardware configuration change?
4. Trade-off between Power and Performance?
5. Temperature, heat, peak power and cumulative power?
Mirabilis_Design AMD Versal System-Level IP LibraryDeepak Shankar
Mirabilis Design provides the VisualSim Versal Library that enable System Architect and Algorithm Designers to quickly map the signal processing algorithms onto the Versal FPGA and define the Fabric based on the performance. The Versal IP support all the heterogeneous resource.
Design and Implementation of Low Power DSP Core with Programmable Truncated V...ijsrd.com
The programmable truncated Vedic multiplication is the method which uses Vedic multiplier and programmable truncation control bits and which reduces part of the area and power required by multipliers by only computing the most-significant bits of the product. The basic process of truncation includes physical reduction of the partial product matrix and a compensation for the reduced bits via different hardware compensation sub circuits. These results in fixed systems optimized for a given application at design time. A novel approach to truncation is proposed, where a full precision vedic multiplier is implemented, but the active section of the truncation is selected by truncation control bits dynamically at run-time. Such architecture brings together the power reduction benefits from truncated multipliers and the flexibility of reconfigurable and general purpose devices. Efficient implementation of such a multiplier is presented in a custom digital signal processor where the concept of software compensation is introduced and analyzed for different applications. Experimental results and power measurements are studied, including power measurements from both post-synthesis simulations and a fabricated IC implementation. This is the first system-level DSP core using a high speed Vedic truncated multiplier. Results demonstrate the effectiveness of the programmable truncated MAC (PTMAC) in achieving power reduction, with minimum impact on functionality for a number of applications. On comparison with the previous parallel multipliers Vedic should be much more fast and area should be reduced. Programmable truncated Vedic multiplier (PTVM) should be the basic part implemented for the arithmetic and PTMAC units.
Hardware Architecture for Calculating LBP-Based Image Region DescriptorsMarek Kraft
In this paper, an efficient hardware architecture, enabling the computation of LBP-based image region descriptors is presented. The complete region descriptor is formed by combining individual local descriptors and arranging them into a grid, as typically used in object detection and recognition. The proposed solution performs massively parallel, pipelined computations, facilitating the processing of over two hundred VGA frames per second and can easily be adopted to different window and grid sizes for the use of other descriptors.
Basic description about how to do a Space Project, based on experiences with XaTcobeo cubesat, a University of Vigo project for ESA education, with the help of INTA.
License: Breogan Costa, University of Vigo, CERN, JINR.
Microarchitecture of a coarse grain out-of-order superscalar processorecway
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects in Chennai, 2013 IEEE JAVA, .NET Projects in Trichy, 2013 IEEE JAVA, .NET Projects in Karur, 2013 IEEE JAVA, .NET Projects in Erode, 2013 IEEE JAVA, .NET Projects in Madurai, 2013 IEEE JAVA, .NET Projects in Salem, 2013 IEEE JAVA, .NET Projects in Coimbatore, 2013 IEEE JAVA, .NET Projects in Tirupur, 2013 IEEE JAVA, .NET Projects in Bangalore, 2013 IEEE JAVA, .NET Projects in Hydrabad, 2013 IEEE JAVA, .NET Projects in Kerala, 2013 IEEE JAVA, .NET Projects in Namakkal, IEEE JAVA, .NET Image Processing, IEEE JAVA, .NET Face Recognition, IEEE JAVA, .NET Face Detection, IEEE JAVA, .NET Brain Tumour, IEEE JAVA, .NET Iris Recognition, IEEE JAVA, .NET Image Segmentation, Final Year JAVA, .NET Projects in Pondichery, Final Year JAVA, .NET Projects in Tamilnadu, Final Year JAVA, .NET Projects in Chennai, Final Year JAVA, .NET Projects in Trichy, Final Year JAVA, .NET Projects in Erode, Final Year JAVA, .NET Projects in Karur, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Tirunelveli, Final Year JAVA, .NET Projects in Madurai, Final Year JAVA, .NET Projects in Salem, Final Year JAVA, .NET Projects in Tirupur, Final Year JAVA, .NET Projects in Namakkal, Final Year JAVA, .NET Projects in Tanjore, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Bangalore, Final Year JAVA, .NET Projects in Hydrabad, Final Year JAVA, .NET Projects in Kerala, Final Year JAVA, .NET IEEE Projects in Pondichery, Final Year JAVA, .NET IEEE Projects in Tamilnadu, Final Year JAVA, .NET IEEE Projects in Chennai, Final Year JAVA, .NET IEEE Projects in Trichy, Final Year JAVA, .NET IEEE Projects in Erode, Final Year JAVA, .NET IEEE Projects in Karur, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Tirunelveli, Final Year JAVA, .NET IEEE Projects in Madurai, Final Year JAVA, .NET IEEE Projects in Salem, Final Year JAVA, .NET IEEE Projects in Tirupur, Final Year JAVA, .NET IEEE Projects in Namakkal, Final Year JAVA, .NET IEEE Projects in Tanjore, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Bangalore, Final Year JAVA, .NET IEEE Projects in Hydrabad, Final Year JAVA, .NET IEEE Projects in Kerala, Final Year IEEE MATLAB Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE MATLAB Projects, Academic Final Year IEEE MATLAB Projects 2013, Academic Final Year IEEE MATLAB Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB
This Virtual User Group session, held on 2014-01-22, presents some of the techniques and algorithms used to improve the CPLEX MIP solver in versions 12.5.1 and 12.6.
Model Compression (NanheeKim)
@NanheeKim @nh9k
질문이 있으면 언제든지 연락주세요!
공부한 것을 바탕으로 작성한 ppt입니다.
출처는 슬라이드 마지막에 있습니다!
Please, feel free to contact me, if you have any questions!
github: https://github.com/nh9k
email: kimnanhee97@gmail.com
byteLAKE's expertise across NVIDIA architectures and configurationsbyteLAKE
AI Solutions for Industries | Quality Inspection | Data Insights | AI-accelerated CFD | Self-Checkout | byteLAKE.com
byteLAKE: Empowering Industries with AI Solutions. Embrace cutting-edge technology for advanced quality inspection, data insights, and more. Harness the potential of our CFD Suite, accelerating Computational Fluid Dynamics for heightened productivity. Unlock new possibilities with Cognitive Services: image analytics for precise visual inspection for Manufacturing, sound analytics enabling proactive maintenance for Automotive, and wet line analytics for the Paper Industry. Seamlessly convert data into actionable insights using Data Insights' AI module, enabling advanced predictive maintenance and risk detection. Simplify Restaurant and Retail operations with our efficient self-checkout solution, recognizing meals and groceries and elevating customer satisfaction. Custom AI Development services available for tailored solutions. Discover more at www.byteLAKE.com.
How to achieve 95%+ Accurate power measurement during architecture exploration? Deepak Shankar
During the conceptualization and architectural exploration phases, it is crucial to assess the power budget.
Would you like to accurately measure the:
1. Power consumed for a proposed embedded software or firmware?
2. Savings of a Power Management Algorithm prior to development?
3. Power impact of hardware configuration change?
4. Trade-off between Power and Performance?
5. Temperature, heat, peak power and cumulative power?
Mirabilis_Design AMD Versal System-Level IP LibraryDeepak Shankar
Mirabilis Design provides the VisualSim Versal Library that enable System Architect and Algorithm Designers to quickly map the signal processing algorithms onto the Versal FPGA and define the Fabric based on the performance. The Versal IP support all the heterogeneous resource.
Mechanical Simulations for Electronic ProductsAnsys
As electronic devices become smaller and more ubiquitous, the printed circuit boards and components that drive them face increasing power densities and evermore complexity. To ensure product reliability and performance, accurate and detailed analysis methodologies are necessary.
The increasing demand for computing power in fields such as biology, finance, machine learning is pushing the adoption of reconfigurable hardware in order to keep up with the required performance level at a sustainable power consumption. Within this context, FPGA devices represent an interesting solution as they combine the benefits of power efficiency, performance and flexibility. Nevertheless, the steep learning curve and experience needed to develop efficient FPGA-based systems represents one of the main limiting factor for a broad utilization of such devices.
In this talk, we present CAOS, a framework which helps the application designer in identifying acceleration opportunities and guides through the implementation of the final FPGA-based system. The CAOS platform targets the full stack of the application optimization process, starting from the identification of the kernel functions to accelerate, to the optimization of such kernels and to the generation of the runtime management and the configuration files needed to program the FPGA.
The increasing demand for computing power in fields such as biology, finance, machine learning is pushing the adoption of reconfigurable hardware in order to keep up with the required performance level at a sustainable power consumption. Within this context, FPGA devices represent an interesting solution as they combine the benefits of power efficiency, performance and flexibility. Nevertheless, the steep learning curve and experience needed to develop efficient FPGA-based systems represents one of the main limiting factor for a broad utilization of such devices.
In this talk, we present CAOS, a framework which helps the application designer in identifying acceleration opportunities and guides through the implementation of the final FPGA-based system. The CAOS platform targets the full stack of the application optimization process, starting from the identification of the kernel functions to accelerate, to the optimization of such kernels and to the generation of the runtime management and the configuration files needed to program the FPGA.
A common need in system architecture design is to verify that if the architect is correct and can satisfy its requirements.
Execution of system architect model means to interact with state machines to test system’s control logic. It can verify if the logical sequences of functions and interfaces in different scenarios are desired.
However, only sequence itself is not enough to verify its consequence or output. So we need each function to do what it is supposed to do during model execution to verify its output, and that is what we called “simulation”.
This presentation introduced how to embed Python or MATLAB® codes inside functions to do “simulation” within Capella.
PSIM pushes the possibilities of power electronics. Discover how engineers in more than 70 countries have used PSIM to design and simulate power electronics.
Similar to Optimization of Electrical Machines in the Cloud with SyMSpace by LCM (20)
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
2. NAFEMS
SyMSpace Simulation Environment
SyMSpace
Center
COMPONENT
SPACE
WEB
INTERFACE
TOOL SPACE
COMPUTING
RESOURCES
Center slave /
Tool slaves
Storage
database
interface
model
configurator
data
visualization
multi-parameter
optimization
academia business
open-source-
community
rotor
dynamicsmagnetic bearing
PMSM
design
pump design
antenna design
ANSYS
CAD
Software
X2C
HOTINT
MODELICA
Cloud resources: amazon,
Cloudsigma, ...
Local CPU
JKU-LCM cluster
3. NAFEMS
SyMSpace Center
• Add simulation components to
project structure
• Configure and control component
interaction
• Create user defined functions,
customized post-processing, extra
visualizations, etc.
DetailbereichModellbaum,
Wertedarstellung
Designvarianten
Mitteilungsbereich
Model tree,
parameter setting
Design variants
Detail view
Log area,
python console
4. NAFEMS
Setup of Simulation Workflow
• Setup of a project with predefined simulation
Components.
• Simulation Components are available for various fields
of engineering.
• Simulation chains can be set up by combining
Components.
8. NAFEMS
Simulation of Permanent Magnet Synchronous
Machines (PMSM)
• Winding is designed fully automatically.
• To speed up simulation only a sector is calculated based on the winding design.
• Example: 12 slots, 5 pol pairs, 3 phases
Negative symmetry is used for simulation
12. NAFEMS
Motor Model for fast Simulation: MagTwin
• Interpolation of simulated flux in dq-rotor reference frame with radial basis functions (RBF) of
the form:
• For functions of two variables
the thin-plate spline kernel is used
with
• Linear term
13. NAFEMS
Motor Model for fast Simulation: MagTwin
Specification
– Generalized Digital Twin which implements the physical behavior of an electromagnetic
system
Model
– Functional Mockup Unit implementation
Steady State Analysis Transient Simulation
14. NAFEMS
AC Loss Calculation (I)
Proximity losses in slot area
– Losses due to PM excitation
are included
– Displacement currents are considered
Losses in parallel wires
– E.g. insert winding with parallel wires
B
worst case
distribution
realistic
distribution
15. NAFEMS
AC Loss Calculation (II)
Eddy current losses caused by PWM modulation
– Includes losses in laminated stack, wires, permanent magnet, solid materials, …
16. NAFEMS
Multiphysics Simulations for PMSM
Rotor stress simulation
– Calculation of rotor stress due to
centrifugal force and shrink fit
– Evaluation stress, strain,
plastic deformation and
transmittable torque
Thermal simulation
– Steady-state heat conduction with
finite element analysis
– Thermal networks to consider 3D effects
Rotor stress distribution
StressMises/N/m2
18. NAFEMS
Multi-Objective Optimization (II)
Pareto optimal design
Pareto optimal solution:
A solution is Pareto optimal if there
exists no feasible solution for
which an improvement in one
objective does not lead to a
simultaneous degradation in one
(or more) of the other objectives.
Pareto
optimal designs
Material
Costs
Verluste
Design variants
Losses
Solution space
19. NAFEMS
Multi-Objective Optimization Algorithms
• Grid
Calculates any possible parameter combination.
Requires huge amount of calculation power
• Generational NSGA-II
(Non-dominated Sorting Genetic Algorithm II)
Steady State Async NSGA-II
• Generational SPEA2
(Strength Pareto Evolutionary Algorithm 2)
Steady State Async SPEA2
• DECMO
(Differential Evolution-based, Coevolutionary
Multi-objective Optimization algorithm)
see next page
Generation based vs. steady state
algorithm
21. NAFEMS
Hybrid Optimization Method
For complex simulations a surrogate model based on
artificial neural networks (ANNs) is created.
This surrogate model is created during the
optimization fully automatic on-the-fly.
Optimization speed can significantly
be improved.
22. NAFEMS
Cluster on demand portal
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Created & owned by LCM
Accessed by LCM customers
(end users): engineers
Created by cloudSME,
hosted by LCM
accessed by LCM staff
Hosted by cloudSME in Germany
Accessed by LCM & cloudSME staff
25. NAFEMS
Thanks for your interest!
Responsible for SyMSpace
LINZ CENTER OF MECHATRONICS GMBH
Science Park I
Altenberger Straße 66
4040 Linz
Austria
+43 732 2468-6002
office@lcm.at
www.lcm.at
Responsible for the cloud concept &
technology:
CloudSME UG
TecTower
Bismarckstr. 142
47057 Duisburg
Germany
+49 203 3639 9955
ocklenburg@cloudsme.eu
www.cloudsme.eu
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