- 소개
2018년 11월 2일, Tech Meets Startup 발표자료
http://tech-startup.kr/
- 발표 제목: 글로벌 격전지에서 발견한 기회 : 기술 스타트업을 위한 궁극의 엔지니어링
- 발표자: FuriosaAI 백준호 CEO
- 내용: AI 반도체를 개발하고 있는 FuriosaAI가 글로벌 기업들의 틈에서 어떻게 기회를 발견하고, 스스로의 존재감을 만들어내고 있는지를 소개합니다. 치열한 경쟁 속에서 고군분투하는 여러 기술 스타트업에 도움되는 세션이길 바랍니다.
(Letsee) Company Introduction ver 2019_06_17JEONG HAN Eom
Letsee is AR startup from S.Korea. You can enjoy AR contents with out App install.
please contact LetSee ( mail : intnoma@letsee.io )
http://www.letsee.io/
Deep learning at supercomputing scale by Rangan Sukumar from CrayBill Liu
Presented at AI NEXTCon Seattle 1/17-20, 2018
http://aisea18.xnextcon.com
join our free online AI group with 50,000+ tech engineers to learn and practice AI technology, including: latest AI news, tech articles/blogs, tech talks, tutorial videos, and hands-on workshop/codelabs, on machine learning, deep learning, data science, etc..
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/feb-2017-member-meeting-rowen
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Chris Rowen of Cognite Ventures delivers the presentation "The Vision AI Start-ups That Matter Most" at the February 2017 Embedded Vision Alliance Member Meeting. Rowen shares his unique perspective on the vision AI start-ups that matter most.
Vertex Perspectives | AI Optimized Chipsets | Part IIIVertex Holdings
In this instalment, we review the training and inference chipset markets, assess the dominance of tech giants, as well as the startups adopting cloud-first or edge-first approaches to AI-optimized chipsets.
(Letsee) Company Introduction ver 2019_06_17JEONG HAN Eom
Letsee is AR startup from S.Korea. You can enjoy AR contents with out App install.
please contact LetSee ( mail : intnoma@letsee.io )
http://www.letsee.io/
Deep learning at supercomputing scale by Rangan Sukumar from CrayBill Liu
Presented at AI NEXTCon Seattle 1/17-20, 2018
http://aisea18.xnextcon.com
join our free online AI group with 50,000+ tech engineers to learn and practice AI technology, including: latest AI news, tech articles/blogs, tech talks, tutorial videos, and hands-on workshop/codelabs, on machine learning, deep learning, data science, etc..
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/feb-2017-member-meeting-rowen
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Chris Rowen of Cognite Ventures delivers the presentation "The Vision AI Start-ups That Matter Most" at the February 2017 Embedded Vision Alliance Member Meeting. Rowen shares his unique perspective on the vision AI start-ups that matter most.
Vertex Perspectives | AI Optimized Chipsets | Part IIIVertex Holdings
In this instalment, we review the training and inference chipset markets, assess the dominance of tech giants, as well as the startups adopting cloud-first or edge-first approaches to AI-optimized chipsets.
As generative AI adoption grows at record-setting speeds and computing demands increase, hybrid processing is more important than ever. But just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices, AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential. In this talk you’ll learn:
• Why on-device AI is key
• Which generative AI models can run on device
• Why the future of AI is hybrid
• Qualcomm Technologies’ role in making hybrid AI a reality
Maximize Big Data ROI via Best of Breed Patterns and PracticesJeff Bertman
******** Abstract: ********
Not long ago the question was whether your organization had big data. Did you have
the volume, the velocity, the technology. Now those basics are largely given for most of
the people attending this event. The path to success is still fuzzy, however, with so many
technologies to choose from – and so many ways to use them.
This presentation triangulates in a holistic manner on the modern business dilemma:
how can we leverage technology to improve revenue, profit, market share, and numerous
other success criteria. That said, this is not about the analytics or KPIs -- although it is
about measurable improvement. It’s about lining up the right technologies and using them
in effective, proven ways to maximize Return on Investment (ROI). Since the slant here
is holistic, we’ll show how to blend infrastructure, tools, methods, and talent to avoid and
constantly trim technical debt… and to produce success stories that are consistently
repeatable, not a byproduct of individual heroics.
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.
General overview of what is "Chaos Engineering", the current
"perturbation models" available and the benefits of Chaos Engineering to Customers, Business and Tech.
Introducing the Vitis Unified Software Platform for Programming FPGAsinside-BigData.com
Since their beginnings, FPGA's have been notorious for being hard to program. That could be changing with the new Vitis Unified Software Platform from Xilinx. Five years in the making, the Vitis unified software platform is designed to allow a whole new user base of software engineers and AI scientists to take advantage of the power of hardware adaptability.
"The Vitis unified software platform automatically tailors the Xilinx hardware architecture to the software or algorithmic code without the need for hardware expertise. Rather than imposing a proprietary development environment, the Vitis platform plugs into common software developer tools and utilizes a rich set of optimized open source libraries, enabling developers to focus on their algorithms. Vitis is separate to the Vivado Design Suite, which will still be supported for those who want to program using hardware code, but Vitis can also boost the productivity of hardware developers by packaging hardware modules as software-callable functions.
With exponentially increasing compute needs, engineers and scientists are often limited by the fixed nature of silicon,” said Victor Peng, president and chief executive officer, Xilinx. “Xilinx has created a singular environment that enables programmers and engineers from all disciplines to co-develop and optimize both their hardware and software, using the tools and frameworks they already know and understand. This means that they can adapt their hardware architecture to their application without the need for new silicon.”
Learn more: https://www.xilinx.com/products/design-tools/vitis.html
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Qualcomm Webinar: Solving Unsolvable Combinatorial Problems with AIQualcomm Research
How do you find the best solution when faced with many choices? Combinatorial optimization is a field of mathematics that seeks to find the most optimal solutions for complex problems involving multiple variables. There are numerous business verticals that can benefit from combinatorial optimization, whether transport, supply chain, or the mobile industry.
More recently, we’ve seen gains from AI for combinatorial optimization, leading to scalability of the method, as well as significant reductions in cost. This method replaces the manual tuning of traditional heuristic approaches with an AI agent that provides a fast metric estimation.
In this presentation you will find out:
Why AI is crucial in combinatorial optimization
How it can be applied to two use cases: improving chip design and hardware-specific compilers
The state-of-the-art results achieved by Qualcomm AI Research
AI for an intelligent cloud and intelligent edge: Discover, deploy, and manag...James Serra
Discover, manage, deploy, monitor – rinse and repeat. In this session we show how Azure Machine Learning can be used to create the right AI model for your challenge and then easily customize it using your development tools while relying on Azure ML to optimize them to run in hardware accelerated environments for the cloud and the edge using FPGAs and Neural Network accelerators. We then show you how to deploy the model to highly scalable web services and nimble edge applications that Azure can manage and monitor for you. Finally, we illustrate how you can leverage the model telemetry to retrain and improve your content.
Workload Transformation and Innovations in POWER Architecture Ganesan Narayanasamy
IT Industry is going through two major transformations. One is adaption of AI and tight integration of the same in the commercial applications and enterprise workflow. Two the transformation in software architecture through the concepts like microservices and the cloud native architecture. These transformation alongside the aggressive adaption of IoT/mobile and 5G in all our day today activities is making the world operate in more real time manner which opens-up a new challenge to improve the hardware architecture to adapt to these requirements. These above two major transformation pushes the boundary of the entire systems stack making the designer rethink hardware. This talk presents you a picture of how the enterprise Industry leading POWER architecture is transforming to fulfill the performance demands of these newer generation workloads with primary focus on the AI acceleration on the chip.
Smart Camera for Non-Intrusive Heart Detectionitaistam
At the recent years there is a rise in vision based applications from autonomous driving to smart cameras that perfect the picture based on the scene. Those application also drove the development of AI accelerators, that can effectively provide the needed computation for the mobile devices. Nevertheless, compared to the future devices, this is just a small glimpse. In this talk we will discuss some of the capabilities of future smart cameras, which today can automatically choose interesting scene or distinct between known people and strangers. However, those cameras can also be used to detect physical health parameters, like heart rate, for reliable and nonintrusive monitoring babies sleep. While some of the capabilities were available via cloud based computation and now this can be done in the node level (when privacy is the main, but not only, benefit of this advancement).
Supermicro AI Pod that’s Super Simple, Super Scalable, and Super AffordableRebekah Rodriguez
The worlds of HPC and AI are evolving at a tremendous rate. The demands of modern-day applications put immense pressure on local IT teams and resources. More often than not, this pressure can come from requiring an AI strategy to speed up mission-critical applications - but this can come at a cost which can hinder adoption. In this webinar, Supermicro, together with International Computer Concepts (ICC) and Define Tech, will demonstrate their AI Super Pod that delivers on AI strategy needs without breaking the bank.
As generative AI adoption grows at record-setting speeds and computing demands increase, hybrid processing is more important than ever. But just like traditional computing evolved from mainframes and thin clients to today’s mix of cloud and edge devices, AI processing must be distributed between the cloud and devices for AI to scale and reach its full potential. In this talk you’ll learn:
• Why on-device AI is key
• Which generative AI models can run on device
• Why the future of AI is hybrid
• Qualcomm Technologies’ role in making hybrid AI a reality
Maximize Big Data ROI via Best of Breed Patterns and PracticesJeff Bertman
******** Abstract: ********
Not long ago the question was whether your organization had big data. Did you have
the volume, the velocity, the technology. Now those basics are largely given for most of
the people attending this event. The path to success is still fuzzy, however, with so many
technologies to choose from – and so many ways to use them.
This presentation triangulates in a holistic manner on the modern business dilemma:
how can we leverage technology to improve revenue, profit, market share, and numerous
other success criteria. That said, this is not about the analytics or KPIs -- although it is
about measurable improvement. It’s about lining up the right technologies and using them
in effective, proven ways to maximize Return on Investment (ROI). Since the slant here
is holistic, we’ll show how to blend infrastructure, tools, methods, and talent to avoid and
constantly trim technical debt… and to produce success stories that are consistently
repeatable, not a byproduct of individual heroics.
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.
General overview of what is "Chaos Engineering", the current
"perturbation models" available and the benefits of Chaos Engineering to Customers, Business and Tech.
Introducing the Vitis Unified Software Platform for Programming FPGAsinside-BigData.com
Since their beginnings, FPGA's have been notorious for being hard to program. That could be changing with the new Vitis Unified Software Platform from Xilinx. Five years in the making, the Vitis unified software platform is designed to allow a whole new user base of software engineers and AI scientists to take advantage of the power of hardware adaptability.
"The Vitis unified software platform automatically tailors the Xilinx hardware architecture to the software or algorithmic code without the need for hardware expertise. Rather than imposing a proprietary development environment, the Vitis platform plugs into common software developer tools and utilizes a rich set of optimized open source libraries, enabling developers to focus on their algorithms. Vitis is separate to the Vivado Design Suite, which will still be supported for those who want to program using hardware code, but Vitis can also boost the productivity of hardware developers by packaging hardware modules as software-callable functions.
With exponentially increasing compute needs, engineers and scientists are often limited by the fixed nature of silicon,” said Victor Peng, president and chief executive officer, Xilinx. “Xilinx has created a singular environment that enables programmers and engineers from all disciplines to co-develop and optimize both their hardware and software, using the tools and frameworks they already know and understand. This means that they can adapt their hardware architecture to their application without the need for new silicon.”
Learn more: https://www.xilinx.com/products/design-tools/vitis.html
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Qualcomm Webinar: Solving Unsolvable Combinatorial Problems with AIQualcomm Research
How do you find the best solution when faced with many choices? Combinatorial optimization is a field of mathematics that seeks to find the most optimal solutions for complex problems involving multiple variables. There are numerous business verticals that can benefit from combinatorial optimization, whether transport, supply chain, or the mobile industry.
More recently, we’ve seen gains from AI for combinatorial optimization, leading to scalability of the method, as well as significant reductions in cost. This method replaces the manual tuning of traditional heuristic approaches with an AI agent that provides a fast metric estimation.
In this presentation you will find out:
Why AI is crucial in combinatorial optimization
How it can be applied to two use cases: improving chip design and hardware-specific compilers
The state-of-the-art results achieved by Qualcomm AI Research
AI for an intelligent cloud and intelligent edge: Discover, deploy, and manag...James Serra
Discover, manage, deploy, monitor – rinse and repeat. In this session we show how Azure Machine Learning can be used to create the right AI model for your challenge and then easily customize it using your development tools while relying on Azure ML to optimize them to run in hardware accelerated environments for the cloud and the edge using FPGAs and Neural Network accelerators. We then show you how to deploy the model to highly scalable web services and nimble edge applications that Azure can manage and monitor for you. Finally, we illustrate how you can leverage the model telemetry to retrain and improve your content.
Workload Transformation and Innovations in POWER Architecture Ganesan Narayanasamy
IT Industry is going through two major transformations. One is adaption of AI and tight integration of the same in the commercial applications and enterprise workflow. Two the transformation in software architecture through the concepts like microservices and the cloud native architecture. These transformation alongside the aggressive adaption of IoT/mobile and 5G in all our day today activities is making the world operate in more real time manner which opens-up a new challenge to improve the hardware architecture to adapt to these requirements. These above two major transformation pushes the boundary of the entire systems stack making the designer rethink hardware. This talk presents you a picture of how the enterprise Industry leading POWER architecture is transforming to fulfill the performance demands of these newer generation workloads with primary focus on the AI acceleration on the chip.
Smart Camera for Non-Intrusive Heart Detectionitaistam
At the recent years there is a rise in vision based applications from autonomous driving to smart cameras that perfect the picture based on the scene. Those application also drove the development of AI accelerators, that can effectively provide the needed computation for the mobile devices. Nevertheless, compared to the future devices, this is just a small glimpse. In this talk we will discuss some of the capabilities of future smart cameras, which today can automatically choose interesting scene or distinct between known people and strangers. However, those cameras can also be used to detect physical health parameters, like heart rate, for reliable and nonintrusive monitoring babies sleep. While some of the capabilities were available via cloud based computation and now this can be done in the node level (when privacy is the main, but not only, benefit of this advancement).
Supermicro AI Pod that’s Super Simple, Super Scalable, and Super AffordableRebekah Rodriguez
The worlds of HPC and AI are evolving at a tremendous rate. The demands of modern-day applications put immense pressure on local IT teams and resources. More often than not, this pressure can come from requiring an AI strategy to speed up mission-critical applications - but this can come at a cost which can hinder adoption. In this webinar, Supermicro, together with International Computer Concepts (ICC) and Define Tech, will demonstrate their AI Super Pod that delivers on AI strategy needs without breaking the bank.
Similar to [TMS 2018] 기술개발 / FuriosaAI 백준호 CEO, 글로벌 격전지에서 발견한 기회 (20)
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
6. Popular Graph: ResNet-50 conv1, input data tensors to the 7x7 convolution on the right of the image in green and
yellow are processed by the convolution vertices into partials (light blue). Reductions (orange) process the partials
and pass on the non-linearity (blue). (Source: Graphcore)
8. Google TPU Pod
64 2nd-gen TPUs
11.5 petaflops
4 terabytes of memory
2-D toroidal mesh network
9. AI Chip Scale of Computation
> 1 Tops > 10 Tops > 100 Tops
1 Tops = 1,000, 000, 000, 000 OP per Second
10. Scale of Storage: Size
Speech/ Vision/Translation High Accuracy Model
> 100MB
Mobile Model
> 1 MB
Recommendation Systems
> 1GB
Mixture of Experts
> 1TB
11. Scale of Storage : Bandwidth
R = 3, W = 112,
N=64, p = 0.2
Fully Connected
3 x 3 Conv
Depthwise
Seperarable Conv
Batch Norm
Layer Norm
Compute
Data Access
Compute / Access
BW per 125 TFLOP
W4 n2
W2 n
W2 n
3 Gb/s 3 Tb/s 30 Tb/s 800 Tb/s
R2 n R2 + n 5
W2 n
W2 r2 n2 W2 r2 n+ W2 n2
W2 n W2 n
5W2 n
(Source : Cerebras)
14. AI Chip
What is the AI chip?
AI chip은 AI computation을 가장 고성능 효율적으로 처리하기 위한 반도체칩이다.
AI chip은 Application + Algorithm + Software + Hardware가 유기적으로 집약된 미래
엔지니어링의 결정체이며, AI 산업의 근본 경쟁력을 결정짓는 요소 기술이다.
Ex: Google TPU, Tesla Autopilot, Alexa AI Speaker
15. AI Chip Global Competition
Competition heating up: vertical & regional
AI chip 시장은 글로벌 기술 격전지이며,
국가별 기업별 vertical 한 방향으로 가고 있다.
Ex: Nvidia, Intel, Google, Amazon, Facebook, Samsung, Qualcomm, ARM, Baidu, Alibaba,
Graphcore, Cerebras, Groq, Cambricon, Horizontal Robotics, Habana…
16. How do we build AI chips?
Weakness & Strength
.
17. How do we build AI chips?
AI 칩 엔지니어링은 많은 요소 기술들이 복합적으로 적용되는 정밀 공학.
Application
Algorithm
Software
Microarchitecture
Verification
Physical Implementation
Manufacturing
Packaging
Testing
Board Design
18. What is the strength of our ecosystem?
AI 칩 제조 경쟁력은 갖추고 있음. Caution: Very Captial Intensive.
Application
Algorithm
Software
Microarchitecture
Verification
Physical Implementation K
Manufacturing J
Packaging J
Testing J
Board Design K
19. What is the weakness of ecosystem?
AI 칩 설계 경쟁력은 글로발 기업에 비해 매우 취약함.
Application L
Algorithm L
Software L
Microarchitecture L
Verification L
Physical Implementation
Manufacturing
Packaging J
Testing J
Board DesignJ
20. Weakness example: Microarchitecture
Microarchitecture가 취약하다는 말은 무엇을 의미하나?
Microarchitecture는 근본 개념설계의 영역이다.
한국 산업 미래를 위한 제언인 책 “축적의 시간”은 근본 개념설계가 우리 인더스터리에 가장 취약한 문제 영역이고,
반드시 극복해야 할 과제로 규정하고 있다.
근본 개념설계는 지성의 힘을 바탕으로 하며 부가가치가 높은 상품으로 이어지는 핵심이다.
퓨리오사는 근본 개념설계에 도전하는 회사이다.
이 다음 슬라이드에서는 Microarchitecture를 정의하고,
근본 개념 설계의 정수인 Microarchitecture 설계 방법론에 대해서 이야기한다.
22. Microarchitecture = micro + architecture
Chip Design회사의 Architecture Blueprint에 기반한 상세 설계도를
FAB회사에 전달 칩을 제조한다.
23. Great architecture needs great architect.
Microarchitecture는 근본 개념설계의 영역이다.
Great building servers people to enable the best human activities in the most humane manner possible given the
building material.
Great microarchitecture serves computation process that enables the best applications in the most efficient
manner possible given the silicon/power/budget
§ Real estate in the micro world
§ Great architect should know in and out of everything and is able to implement the chip as scheduled with
the given budgets
24. Microarchitect’s toolkit
근본 개념 설계는 필드의 근본 개념에 근거해야 한다.
§ Instruction Set Architecture
§ VLIW, SIMD, VECTOR, Systolic Array
§ SuperScale, Multithreading, DataFlow
§ Pipelining
§ Virtualization
§ Prefetching, Caching
§ IO, Memory subsystem
§ Finite State Machine
§ …
27. Build the performance modeling simulator
It’s a so called cycle accurate-simulator which can simulate both behavior and performance of
machine we’re building at the very fine granularity and abstraction level which is usually at the
level of clock cycle. This enforces the discipline of
§ Concrete and precise thinking
§ Data-Driven evaluation for important trade-off of design choices
Architect should have strong (or reasonable) SW skill to build this simulator.
OOP language and Event-Driven programming paradigm is the natural fit for this job. C++ is the
standard choice.
28. Arch exploration takes time and experiences.
Korean industries have neglected this part because we didn’t (or couldn’t afford to) allocate
enough time for defining and exploring the design space to come up with the solid architecture
specification. It takes time because
§ Workload characterization and prediction takes time.
§ Simulation needs supercomputer-scale computation.
§ Understanding very detailed design trade-off just takes time.
In other words, cultivating intuition by refining it iteratively by methodically taking good measures
takes time
29. Time Schedule
So let’s say it takes 1.5~2 years to build commercial AI chips from concept to production. We need
to allocate at least 6~8 month for performance modeling that goes in parallel to the
implementation
Performance Modeling /
Architecturing
RTL Implementation
Software Architecturing / Implementation
Verification
Physical Design / Manufacturing
30. Arch Examples: : Quantization (suggested by Google)
§ Aggressive operator fusion: Performing as many operations as possible in a single pass can
lower the cost of memory accesses and provide significant improvements in run-time and
power consumption
§ Compressed memory access: One can optimize memory bandwidth by supporting on the fly
de-compression of weights (and activations). A simple way to do that is to support lower
precision storage of weights and possibly activations.
§ Lower precision 4/8/16 bit arithmetic processing
§ Per-layer selection of bitwidths
§ Per-channel quantization
34. New Organization Essential
Application (Business) + Algorithm+ Software Driven된 기존과 다른 조직 구성이
필수적으로 필요하다.
Any orgnization that designs a system… will inevitably produce a design whose structure
is a copy of the organization’s communication structure. – Conway, cliff young
• 큰 기업이 스타트업보다 불리함.
• 스타트업에게도 쉽지 않음.
35. FuriosaAI: organization structure
Application + Algorithm + Software Driven
• Application Partners: Naver, BinaryVR, Molocos, Neosapience, Seoul Smart City
Project…
• Algorithm (2)
• Software (6): Compiler, Runtime, Driver, Tool Chains
• Microarchitect (4): NPU Core, NoC, DRAM subsystem
• Logic Design (3)
• Physical Design (1): Outsourcing to SiFive or China Partners
• Manufacturing / Packaging / Board: TSMC or Samsung and Design house.
37. 뜻으로 본 한국 역사 (함석헌)
수난의 여왕
치욕과
분열과
압박과
상실과
좌절을 극복해나가는 역사
한국 기술 스타트업은 글로발 그리고 국내 생태계의 험준한 위치에서
가파른 수난의 지형을 뚫고 올라가는 도전의 걸음임과 동시에
수많은 실패속에서도 결국 분명히 우뚝 서겠다는 강한 의지와 희망이다.
38. 뜻으로 보는 기술 스타트업
새로운 창조를 위한 씨알
씨알의 역사적 의미 - 씨알이란 말은 민(people)이란 뜻인데, 우리 자신을 역사적 악에서
해방시키고, 새로운 창조를 위한 자격을 스스로 닦아 내기 위한 씨알.
기술 스타트업의 생태계적 의미 – 지성(People + AI)을 바탕으로 근본 문제를 해결하여 우리 생태계
(ecosystem)를 기존 관성에서 해방시키고, 혁신적 비지니스 모델 을 창조하기 위한 자격을 스스로
닦아 내기 위한 씨알.
Keyword: 주체성, 근본성, 순수성, 생동성, 관계성
39. Final Word: ecosystem
We should do deep research on local and global Ecosystem.
기술 기업은 필수적으로 기술을 필요로 하는 파트너와 적극 협력하는 관계가 중요하며 이는
국내와 글로발 생태계에 대한 깊은 이해와 더불어 자신에 대한 철저한 인식을 바탕으로 해야
한다.