PL-4089, Accelerating and Evaluating OpenCL Graph Applications, by Shuai Che,...AMD Developer Central
PL-4089, Accelerating and Evaluating OpenCL Graph Applications, by Shuai Che, Bradford Bechmann, Steve Reinhardt and Kevin Skadron at the AMD Developer Summit (APU13) November 11-13, 2014.
IS-4011, Accelerating Analytics on HADOOP using OpenCL, by Zubin Dowlaty and ...AMD Developer Central
Presentation IS-4011, Accelerating Analytics on HADOOP using OpenCL, by Zubin Dowlaty and Krishnaraj Gharpure at the AMD Developer Summit (APU13) November 11-13, 2013.
Axel Koehler from Nvidia presented this deck at the 2016 HPC Advisory Council Switzerland Conference.
“Accelerated computing is transforming the data center that delivers unprecedented through- put, enabling new discoveries and services for end users. This talk will give an overview about the NVIDIA Tesla accelerated computing platform including the latest developments in hardware and software. In addition it will be shown how deep learning on GPUs is changing how we use computers to understand data.”
In related news, the GPU Technology Conference takes place April 4-7 in Silicon Valley.
Watch the video presentation: http://insidehpc.com/2016/03/tesla-accelerated-computing/
See more talks in the Swiss Conference Video Gallery:
http://insidehpc.com/2016-swiss-hpc-conference/
Sign up for our insideHPC Newsletter:
http://insidehpc.com/newsletter
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/movidius/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Sofiane Yous, Principal Scientist in the machine intelligence group at Movidius, presents the "Dataflow: Where Power Budgets Are Won and Lost" tutorial at the May 2016 Embedded Vision Summit.
This presentation showcases stories from the front lines in the battle between power and performance in embedded vision, deep learning and computational imaging applications. First, Youse demonstrates why good dataflow is so important. Also, he shows why modern techniques and APIs are critical for fast time-to-market, and he’ll summarize relevant academic work. He compares the usage models and benefits of such relevant APIs as TensorFlow and classic approaches for deep learning; standards based approaches for computer vision, and techniques such as Halide for imaging and computational photography. He also presents specific examples such as the GoogleNet implementation under Caffe/TensorFlow and other imaging/vision use cases.
NVIDIA CEO Jensen Huang Presentation at Supercomputing 2019NVIDIA
Broadening support for GPU-accelerated supercomputing to a fast-growing new platform, NVIDIA founder and CEO Jensen Huang introduced a reference design for building GPU-accelerated Arm servers, with wide industry backing.
Converged and Containerized Distributed Deep Learning With TensorFlow and Kub...Mathieu Dumoulin
Docker containers running on Kubernetes combine with MapR Converged Data Platform allow any company to potentially enjoy the same sophisticated data infrastructure for enabling teams to engage in transformative machine learning and deep learning for production use at scale.
PL-4089, Accelerating and Evaluating OpenCL Graph Applications, by Shuai Che,...AMD Developer Central
PL-4089, Accelerating and Evaluating OpenCL Graph Applications, by Shuai Che, Bradford Bechmann, Steve Reinhardt and Kevin Skadron at the AMD Developer Summit (APU13) November 11-13, 2014.
IS-4011, Accelerating Analytics on HADOOP using OpenCL, by Zubin Dowlaty and ...AMD Developer Central
Presentation IS-4011, Accelerating Analytics on HADOOP using OpenCL, by Zubin Dowlaty and Krishnaraj Gharpure at the AMD Developer Summit (APU13) November 11-13, 2013.
Axel Koehler from Nvidia presented this deck at the 2016 HPC Advisory Council Switzerland Conference.
“Accelerated computing is transforming the data center that delivers unprecedented through- put, enabling new discoveries and services for end users. This talk will give an overview about the NVIDIA Tesla accelerated computing platform including the latest developments in hardware and software. In addition it will be shown how deep learning on GPUs is changing how we use computers to understand data.”
In related news, the GPU Technology Conference takes place April 4-7 in Silicon Valley.
Watch the video presentation: http://insidehpc.com/2016/03/tesla-accelerated-computing/
See more talks in the Swiss Conference Video Gallery:
http://insidehpc.com/2016-swiss-hpc-conference/
Sign up for our insideHPC Newsletter:
http://insidehpc.com/newsletter
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/movidius/embedded-vision-training/videos/pages/may-2016-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Sofiane Yous, Principal Scientist in the machine intelligence group at Movidius, presents the "Dataflow: Where Power Budgets Are Won and Lost" tutorial at the May 2016 Embedded Vision Summit.
This presentation showcases stories from the front lines in the battle between power and performance in embedded vision, deep learning and computational imaging applications. First, Youse demonstrates why good dataflow is so important. Also, he shows why modern techniques and APIs are critical for fast time-to-market, and he’ll summarize relevant academic work. He compares the usage models and benefits of such relevant APIs as TensorFlow and classic approaches for deep learning; standards based approaches for computer vision, and techniques such as Halide for imaging and computational photography. He also presents specific examples such as the GoogleNet implementation under Caffe/TensorFlow and other imaging/vision use cases.
NVIDIA CEO Jensen Huang Presentation at Supercomputing 2019NVIDIA
Broadening support for GPU-accelerated supercomputing to a fast-growing new platform, NVIDIA founder and CEO Jensen Huang introduced a reference design for building GPU-accelerated Arm servers, with wide industry backing.
Converged and Containerized Distributed Deep Learning With TensorFlow and Kub...Mathieu Dumoulin
Docker containers running on Kubernetes combine with MapR Converged Data Platform allow any company to potentially enjoy the same sophisticated data infrastructure for enabling teams to engage in transformative machine learning and deep learning for production use at scale.
Accelerate AI w/ Synthetic Data using GANsRenee Yao
Strata Data Conference in Sep 2018 Presentation
Description:
Synthetic data will drive the next wave of deployment and application of deep learning in the real world across a variety of problems involving speech recognition, image classification, object recognition and language. All industries and companies will benefit, as synthetic data can create conditions through simulation, instead of authentic situations (virtual worlds enable you to avoid the cost of damages, spare human injuries, and other factors that come into play); unparalleled ability to test products, and interactions with them in any environment.
Join us for this introductory session to learn more about how Generative Adversarial Networks (GAN) are successfully used to improve data generation. We will cover specific real-world examples where customers have deployed GAN to solve challenges in healthcare, space, transportation, and retail industries.
Renee Yao explains how generative adversarial networks (GAN) are successfully used to improve data generation and explores specific real-world examples where customers have deployed GANs to solve challenges in healthcare, space, transportation, and retail industries.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
An overview and update of our hardware and software offering and support provided to the Machine & Deep Learning Community around the world.
Alison B. Lowndes, AI DevRel, EMEA
Kicking off the first in a series of global GPU Technology Conferences, NVIDIA co-founder and CEO Jen-Hsun Huang today at GTC China unveiled technology that will accelerate the deep learning revolution that is sweeping across industries. Huang spoke in front of a crowd of more than 2,500 scientists, engineers, entrepreneurs and press, gathered in Beijing for a day devoted to deep learning and AI. On stage he announced the Tesla P4 and P40 GPU accelerators for inferencing production workloads for AI services and, a small, energy-efficient AI supercomputer for highway driving — the NVIDIA DRIVE PX 2 for AutoCruise.
State of the Art Robot Predictive Maintenance with Real-time Sensor DataMathieu Dumoulin
Our Strata Beijing 2017 presentation slides where we show how to use data from a movement sensor, in real-time, to do anomaly detection at scale using standard enterprise big data software.
Nvidia Deep Learning Solutions - Alex SabatierSri Ambati
Alex Sabatier from Nvidia talks about the future of Deep Learning from an chipmaker perspective
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Simplifying AI Infrastructure: Lessons in Scaling on DGX SystemsRenee Yao
Simplifying AI Infrastructure: Lessons in Scaling on DGX Systems, the world's most powerful AI Systems. This is a presentation I did at GTC Israel in 2018
MapR is an ideal scalable platform for data science and specifically for operationalizing machine learning in the enterprise. This presentations gives specific reasons why.
The Visual Computing Company
Por Margio Aguiar
PSG LATAM Manager
NVIDIA
Panorama sobre las ventajas de la tecnología de visualización en materia de cómputo para diferentes giros empresariales, ventaja competitiva y operativa ofertada por NVIDIA.
Learn about what technologies enable a new, modern Stream-based architecture to connect everything within application modules or across data centers and public clouds. Combine Kafka-style streaming and stream processing frameworks like Spark and Flink with Microservices and completely rethink your big data architecture away from state and into data flows.
This is a presentation I presented at NVIDIA AI Conference in Korea. It's about building the largest GPU - DGX-2, the most powerful supercomputer in one node.
Accelerate AI w/ Synthetic Data using GANsRenee Yao
Strata Data Conference in Sep 2018 Presentation
Description:
Synthetic data will drive the next wave of deployment and application of deep learning in the real world across a variety of problems involving speech recognition, image classification, object recognition and language. All industries and companies will benefit, as synthetic data can create conditions through simulation, instead of authentic situations (virtual worlds enable you to avoid the cost of damages, spare human injuries, and other factors that come into play); unparalleled ability to test products, and interactions with them in any environment.
Join us for this introductory session to learn more about how Generative Adversarial Networks (GAN) are successfully used to improve data generation. We will cover specific real-world examples where customers have deployed GAN to solve challenges in healthcare, space, transportation, and retail industries.
Renee Yao explains how generative adversarial networks (GAN) are successfully used to improve data generation and explores specific real-world examples where customers have deployed GANs to solve challenges in healthcare, space, transportation, and retail industries.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
An overview and update of our hardware and software offering and support provided to the Machine & Deep Learning Community around the world.
Alison B. Lowndes, AI DevRel, EMEA
Kicking off the first in a series of global GPU Technology Conferences, NVIDIA co-founder and CEO Jen-Hsun Huang today at GTC China unveiled technology that will accelerate the deep learning revolution that is sweeping across industries. Huang spoke in front of a crowd of more than 2,500 scientists, engineers, entrepreneurs and press, gathered in Beijing for a day devoted to deep learning and AI. On stage he announced the Tesla P4 and P40 GPU accelerators for inferencing production workloads for AI services and, a small, energy-efficient AI supercomputer for highway driving — the NVIDIA DRIVE PX 2 for AutoCruise.
State of the Art Robot Predictive Maintenance with Real-time Sensor DataMathieu Dumoulin
Our Strata Beijing 2017 presentation slides where we show how to use data from a movement sensor, in real-time, to do anomaly detection at scale using standard enterprise big data software.
Nvidia Deep Learning Solutions - Alex SabatierSri Ambati
Alex Sabatier from Nvidia talks about the future of Deep Learning from an chipmaker perspective
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Simplifying AI Infrastructure: Lessons in Scaling on DGX SystemsRenee Yao
Simplifying AI Infrastructure: Lessons in Scaling on DGX Systems, the world's most powerful AI Systems. This is a presentation I did at GTC Israel in 2018
MapR is an ideal scalable platform for data science and specifically for operationalizing machine learning in the enterprise. This presentations gives specific reasons why.
The Visual Computing Company
Por Margio Aguiar
PSG LATAM Manager
NVIDIA
Panorama sobre las ventajas de la tecnología de visualización en materia de cómputo para diferentes giros empresariales, ventaja competitiva y operativa ofertada por NVIDIA.
Learn about what technologies enable a new, modern Stream-based architecture to connect everything within application modules or across data centers and public clouds. Combine Kafka-style streaming and stream processing frameworks like Spark and Flink with Microservices and completely rethink your big data architecture away from state and into data flows.
This is a presentation I presented at NVIDIA AI Conference in Korea. It's about building the largest GPU - DGX-2, the most powerful supercomputer in one node.
Presentation from Chesapeake Regional Tech Council\'s TechFocus Seminar on Cloud Security; Presented by Scott C Sadler, Business Development Executive - Cloud Computing, IBM US East Mid-Market & Channels on Thursday, October 27, 2011. http://www.chesapeaketech.org
Imaging in the Cloud: A New Era for RadiologyCarestream
A look at how cloud computing is helping the medical imaging industry. The cloud is changing old mindsets, and allowing technologies, such as a vendor-neutral archive (VNA), to make health facilities more efficient and provide higher quality care.
Rapid advances in technology has led to the amalgamation of two very powerful technologies, mobile and the cloud. This presentation highlights its importance in healthcare
Health IT Summit DC 2015 - Cloud Storage and Medical Image Management: Responding to the filesize increases of advanced imaging technologies
Todd Thomas
CIO
Austin Radiological Association
iHT2 case studies and presentations illustrate challenges, successes, and various factors in the outcomes of numerous types of health IT implementations. They are interactive and dynamic sessions providing opportunity for dialogue, debate and exchanging ideas and best practices. This session will be presented by a thought leader in the provider, payer or government space.
Cloud eHealth in Medical Imaging & RadiologyCarestream
Cloud computing in medical imaging, with real life examples. Presentation given by Pierre Yves Nectoux, at the World of Health IT congress, in Barcelona Spain, on 15 March 2010. Presentation includes two case studies, as well as a general implementation example.
For more on the cloud, visit http://www.carestream.com/cloud
DriCloud. Cloud based Electronic Medical Recorddricloud
EHR - Cloud based practice Management Software for medical clinics and healthcare providers. DriCloud is an easy and intuitive that adapts to the way you work
In the AWS Healthcare Days presentation you’ll learn best practices for architecting cloud-based applications for the healthcare industry with a deep technical overview and demos. Topics to be covered in this presentation include building a healthcare analytics pipeline in the cloud, HIPAA-compliant storage and archiving, and Using infrastructure-as-code to automate your security and compliance policies. You will also see how cloud security partner, Clear DATA, is helping healthcare providers leverage services like AWS Config and AWS CloudTrail, as well as, system level tooling to maintain the security and compliance of applications and environments through automation.
IoT is a combination of hardware and software technology that produces trillions of data through connecting multiple devices and sensors with the cloud and making sense of data with intelligent tools
IoT in Healthcare is a heterogeneous computing, wirelessly communicating system of apps and devices that connects patients and health providers to diagnose, monitor, track and store vital statistics and medical information.
Strategic Uses for Cost Efficient Long-Term Cloud StorageAmazon Web Services
Compared to storing long-term datasets on-premises, archiving in the cloud is a smart alternative whether you’re looking for an active archive solution, tape replacement, or to fulfill a compliance requirement. Learn how AWS customers are simplifying their archiving strategy and meeting compliance needs using Amazon Glacier. Hear how customers have evolved their backup and disaster recovery architectures and replaced tape solutions by turning to AWS for a more cost efficient, durable and agile solution. We will showcase Sony DADC's active archive deployment on Glacier and demo how some of our financial service customers have set up compliant archives to meet their regulatory objectives.
Know how GPUs have become the de-facto standard for AI workloads for infrastructure transformation. Also, understand the importance of Machine Learning and Deep learning in this fast pacing tech-world.
Here in these slides we are going to discuss about the Digital pathology in which we have discuss about the working, role, benefits and requirements of Digital pathology.
Virtual Human Brain Simulations with Abaqus in the CloudThe UberCloud
UberCloud, Dassault Systèmes Simulia and Advania Data Centers presentation about the award winning project: HPC Cloud Simulation of Neuromodulation in Schizophrenia. Learn how simulation and high performance computing in the cloud play a key role in accelerating personalized healthcare.
The Brain Neuromodulation project represents a breakthrough in demonstrating the high value of computational modeling and simulation in improving the clinical application of non-invasive electro-stimulation of the human brain in schizophrenia and the potential to apply this technology to the treatment of other neuropsychiatric disorders such as depression and Parkinson’s disease. With the addition of HPC, clinicians can now precisely and non-invasively target regions of the brain without disrupting nearby healthy brain regions.
2018 Hyperion HPC Innovation Excellence Award: UberCloud, the National Institute of Mental Health & Neuro Sciences (NIMHANS) in Bangalore, Dassault Systèmes Simulia, Advania Data Centers, Hewlett Packard Enterprise and Intel won the 2018 Hyperion HPC Innovation Excellence Award for their Neuromodulation Project, based on computer simulations of non-invasive transcranial electro-stimulation of the human brain in schizophrenia.
The era of cloud and mobility has changed the way we work and transformed the internet into the transport network for most enterprises. Even so, many continue to rely on security technologies designed for the old world, when users and data were on the network and applications were housed in the data center.
ESG believes that the challenge of using legacy security methods in the cloud era will be a key catalysts for the adoption of a new user- and application-centric approach known as zero trust security. The zero trust model is enabled by the software-defined perimeter (SDP), delivering secure anywhere access to internal applications without the use of VPN technology.
Cloud-Based Solutions for Clinical Data ManagementClinosolIndia
Cloud-based solutions have become increasingly popular in the field of clinical data management due to their scalability, accessibility, cost-effectiveness, and potential for collaboration. These solutions offer a range of benefits for managing and analyzing clinical data while ensuring security and compliance with regulatory requirements such as HIPAA. Here are some key cloud-based solutions for clinical data management
Diabetic retinopathy (DR) is one of the most common causes of blindness. The necessity for a robust and automated DR screening system for regular examination has long been recognized in order to identify DR at an early stage. In this paper, an embedded DR diagnosis system based on convolutional neural networks (CNNs) has been proposed to assess the proper stage of DR. We coupled the power of CNN with transfer learning to design our model based on state-of-the-art architecture. We preprocessed the input data, which is color fundus photography, to reduce undesirable noise in the image. After training many models on the dataset, we chose the adopted ResNet50 because it produced the best results, with a 92.90% accuracy. Extensive experiments and comparisons with other research work show that the proposed method is effective. Furthermore, the CNN model has been implemented on an embedded target to be a part of a medical instrument diagnostic system. We have accelerated our model inference on a field programmable gate array (FPGA) using Xilinx tools. Results have confirmed that a customized FPGA system on chip (SoC) with hardware accelerators is a promising target for our DR detection model with high performance and low power consumption.
Given the data center industry’s cagey nature – the secrecy around critical infrastructure, the NDAs, and so on – we can’t make specific predictions without substantial risk of looking like total fools. But from conversations with vendors and analysts we can at a minimum get some idea of the directions data center technologies are moving in.
Digital supply chain quality managementMartin Geddes
We've figured out how to send physical goods around the world: aggregate them into containers. We're still struggling how to do digital good, which we disaggregate into packets. Here's the answer.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
Unlocking the Power of Data: Data Driven Product Engineering, Evren Eryurek, ...Zinnov
We live in a data-rich world - almost everything we do is being captured and stored somewhere. There are algorithms crunching the data every millisecond and conveying unknown and untapped information. At an enterprise level, data analytics provides us a 360-degree view of our customers, products and the business landscape to make effective, smart decisions. This presentation delves into how the traditional business philosophy of ‘proximity to customer’ will lose its significance and how data will drive product decisions.
Vulkan and DirectX12 share many common concepts, but differ vastly from the APIs most game developers are used to. As a result, developing for DX12 or Vulkan requires a new approach to graphics programming and in many cases a redesign of the Game Engine. This lecture will teach the basic concepts common to Vulkan and DX12 and help developers overcome the main problems that often appear when switching to one of the new APIs. It will explain how those new concepts will help games utilize the hardware more efficiently and discuss best practices for game engine development.
For more, visit http://developer.amd.com/
AMD’s math libraries can support a range of programmers from hobbyists to ninja programmers. Kent Knox from AMD’s library team introduces you to OpenCL libraries for linear algebra, FFT, and BLAS, and shows you how to leverage the speed of OpenCL through the use of these libraries.
Review the material presented in the AMD Math libraries webinar in this deck.
For more:
Visit the AMD Developer Forums:http://devgurus.amd.com/welcome
Watch the replay: www.youtube.com/user/AMDDevCentral
Follow us on Twitter: https://twitter.com/AMDDevCentral
This is the slide deck from the popular "Introduction to Node.js" webinar with AMD and DevelopIntelligence, presented by Joshua McNeese. Watch our AMD Developer Central YouTube channel for the replay at https://www.youtube.com/user/AMDDevCentral.
This presentation accompanies the webinar replay located here: http://bit.ly/1zmvlkL
AMD Media SDK Software Architect Mikhail Mironov shows you how to leverage an AMD platform for multimedia processing using the new Media Software Development Kit. He discusses how to use a new set of C++ interfaces for easy access to AMD hardware blocks, and shows you how to leverage the Media SDK in the development of video conferencing, wireless display, remote desktop, video editing, transcoding, and more.
An Introduction to OpenCL™ Programming with AMD GPUs - AMD & Acceleware WebinarAMD Developer Central
This deck presents highlights from the Introduction to OpenCL™ Programming Webinar presented by Acceleware & AMD on Sept. 17, 2014. Watch a replay of this popular webinar on the AMD Dev Central YouTube channel here: https://www.youtube.com/user/AMDDevCentral or here for the direct link: http://bit.ly/1r3DgfF
Learn more about DirectGMA in this blog post: bit.ly/AMDDirectGMA
AMD has introduced Direct Graphics Memory Access in order to:
‒ Makes a portion of the GPU memory accessible to other devices
‒ Allows devices on the bus to write directly into this area of GPU memory
‒ Allows GPUs to write directly into the memory of remote devices on the bus supporting DirectGMA
‒ Provides a driver interface to allow 3rd party hardware vendors to support data exchange with an AMD GPU using DirectGMA
‒ and more
View the accompanying blog post here: bit.ly/AMDDirectGMA
This Webinar explores a variety of new and updated features in Java 8, and discuss how these changes can positively impact your day-to-day programming.
Watch the video replay here: http://bit.ly/1vStxKN
Your Webinar presenter, Marnie Knue, is an instructor for Develop Intelligence and has taught Sun & Oracle certified Java classes, RedHat JBoss administration, Spring, and Hibernate. Marnie also has spoken at JavaOne.
The Small Batch (and other) solutions in Mantle API, by Guennadi Riguer, Mant...AMD Developer Central
This presentation discusses the Mantle API, what it is, why choose it, and abstraction level, small batch performance and platform efficiency.
Download the presentation from the AMD Developer website here: http://bit.ly/TrEUeC
Inside XBox One by Martin Fuller from the Sweden Game Developers Conference, June 2, 2014, Stockholm, Sweden. View other presentations here: http://bit.ly/TrEUeC
Computer Vision Powered by Heterogeneous System Architecture (HSA) by Dr. Ha...AMD Developer Central
Computer Vision Powered by Heterogeneous System Architecture (HSA) by Dr. Harris Gasparakis, AMD, at the Embedded Vision Alliance Summit, May 2014.
Harris Gasparakis, Ph.D., is AMD’s OpenCV manager. In addition to enhancing OpenCV with OpenCL acceleration, he is engaged in AMD’s Computer Vision strategic planning, ISVs, and AMD Ventures engagements, including technical leadership and oversight in the AMD Gesture product line. He holds a Ph.D. in theoretical high energy physics from YITP at SUNYSB. He is credited with enabling real-time volumetric visualization and analysis in Radiology Information Systems (Terarecon), including the first commercially available virtual colonoscopy system (Vital Images). He was responsible for cutting edge medical technology (Biosense Webster, Stereotaxis, Boston Scientific), incorporating image and signal processing with AI and robotic control.
Productive OpenCL Programming An Introduction to OpenCL Libraries with Array...AMD Developer Central
In this webinar presentation, ArrayFire COO Oded Green demonstrates best practices to help you quickly get started with OpenCL™ programming. Learn how to get the best performance from AMD hardware in various programming languages using ArrayFire. Oded discusses the latest advancements in the OpenCL™ ecosystem, including cutting edge OpenCL™ libraries such as clBLAS, clFFT, clMAGMA and ArrayFire. Examples are shown in real code for common application domains.
Watch the webinar here: http://bit.ly/1obT0M2
For more developer resources, visit:
http://arrayfire.com/
http://developer.amd.com/
Follow us on Twitter: https://twitter.com/AMDDevCentral
See info in the slides for more contact information and resource links!
Rendering Battlefield 4 with Mantle by Johan Andersson - AMD at GDC14AMD Developer Central
Johan Andersson will show how the Frostbite 3 game engine is using the low-level graphics API Mantle to deliver significantly improved performance in Battlefield 4 on PC and future games from Electronic Arts in this presentation from the 2014 Game Developers Conference in San Francisco March 17-21. Also view this and other presentations on our developer website at http://developer.amd.com/resources/documentation-articles/conference-presentations/
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.
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
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
3. OPPORTUNITY
TO
IMPROVE
PATIENT
CARE
MEDICAL
IMAGING
MARKET
! US
spends
$100B
on
520,500,000
medical
scans
!
$3.5B
on
soTware
‒ RIS
CVIS
PACS
!
$1.8B
in
2010
!
3.5%
CAGR
‒ Image
Analysis
!
$1.7B
in
2012
!
7.1%
CAGR
! Why
Scan?
!
early
detecDon
!
survive
‒ e.g.
13M
cancer
paDents
alive
in
2012
! 30,000
radiologists
!
10
minutes/scan
!
limits
diagnosDc
outcome
! Survival
rate
could
be
increased
through
Dmely
physicians
and
paDent
interacDon
! Physicians
and
paDents
need
enhanced
visualizaDons,
computer
aided
diagnosis,
and
social
media
! KJAYA
Medical
has
a
soluDon
3
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
4. MEDICAL
IMAGE
MANAGEMENT
IS
CURRENTLY
ON
PREMISES
PICTURE
ARCHIVING
AND
COMMUNICATION
SYSTEMS
(PACS)
Film
Warehouse
Digital
Warehouse
Onsite
PACS
Specialized
WorkstaDon
4
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
5. CROWDED
MARKET
–
OLDER
TECHNOLOGY
CURRENT
PACS
MARKET
IS
FRAGMENTED
Onsite
PACS
Blue
Ocean
Markets
Cloud
Social
Media
Third
GeneraDon
PACS
Technology
Current
Technology
5
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
6. CURRENT
CLOUD
PACS
MARKET
-‐
LESS
THAN
1%
FOCUSED
ON
NON-‐DIAGNOSTIC
USE
OF
IMAGE
SHARING
AND
OFFSITE
BACKUP
13%
3%
2%
1%
Cloud
Current
Cloud
accounts
about
1%
of
the
market
• $56m
in
2010
expected
to
grow
27%
CAGR
to
2018
• Mostly
in
archival
and
image
sharing
• Third
generaDon
PACS
on
cloud
in
its
infancy
81%
Onsite
Challenges
for
cloud
PACS
• Access
speeds
• DiagnosDc
quality
• Tools
to
manipulate
data
in
real
Dme
6
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
7. PACS
FUTURE
ENTERPRISE
IMAGING
CLOUD
Onsite
PACS
Cloud
based
Enterprise
PACS
Third
generaMon
PACS
requirements
Current
RIS/PACS
• 91%
penetraDon
• 52%
older
than
5
years
• 21%
plan
to
replace
in
12
months
Cardiology
:
60%
have
no
PACS
Pathology:
90%
have
no
PACS
7
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PRESENTATION
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November
22,
2013
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CONFIDENTIAL
• Enterprise
PACS
–
PaDent
centered,
mulD-‐departmental,
integrated
image
management
plalorm
• Cloud
based
–
Strong
ROI,
distributed
mulD-‐site
access
at
speeds
equal
to
on
site
PACS
• Image/report
sharing
with
referring
physicians
and
paDents
on
demand
• Higher
levels
of
funcDonality
-‐
advanced
visualizaDon,
computer
aided
diagnosis
• IntegraDon
with
EHRs,
HIEs
11. DIFFERENTIATED
APPROACH
:
GPU
CLOUD
GPU
CLOUD
BENEFITS
GPU
:
1100
GFLOPS
Real-‐Dme
diagnosDc
quality
visualizaDons
•
On-‐demand
and
real-‐Dme
radiology
•
IntuiDve
results
for
ordering
physicians
•
Connect
with
paDents
CPU
:
90
GFLOPS
11
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TITLE
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November
22,
2013
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CONFIDENTIAL
Faster
and
Affordable
CAD
and
‘Big
Data’
AnalyDcs
•
Improve
accuracy
•
Less
radiaDon
to
paDents
by
reducing
unnecessary
use
of
imaging
•
Streamline
healthcare
and
reduce
costs
12. DIFFERENTIATED
APPROACH
:
GPU
CLOUD
HIGH
DEFINITION
VISUALIZATION
" CPU
Ray
CasDng
(Compromise
Quality
for
Speed)
12
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PRESENTATION
TITLE
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November
22,
2013
|
CONFIDENTIAL
" VoXcell
GPU
Pre-‐integrated
Texturing
13. DIFFERENTIATED
APPROACH
:
GPU
CLOUD
HIGH
DEFINITION
VISUALIZATION
" CPU
Ray
CasDng
(Compromise
Quality
for
Speed)
" VoXcell
GPU
Pre-‐integrated
Texturing
" Real-‐Dme
performance
requires
early
ray
terminaDon
once
opacity
is
reached
(25%)
!
results
in
hard
plasDc
looking
surfaces.
Transparent
surfaces
degrades
performance.
" Real-‐Dme
performance
achieved
through
texture
mapping
polygons
!
results
in
soTer,
more
realisDc
surfaces
that
includes
interior
points.
Enables
transparent
surfaces
13
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
14. DIFFERENTIATED
APPROACH
:
GPU
CLOUD
PREDICTIVE
INTELLIGENT
STREAMING
OVERCOMES
LARGE
DATA
ACCESS
SPEED
AND
LATENCY
OVER
INTERNET
" Use
GPU
to
manipulate
GB
of
paDent
data
remotely
without
transmiqng
data
to
end
user
" Access
visualizaDons
on
any
device
on-‐demand
and
real-‐Dme
" Streaming
visualizaDons
done
by
predicDng
next
frames
" Fast
FPS
from
GPU
enable
discarding
incorrectly
predicted
frames
and
generaDng
new
ones
" Predicted
frames
are
buffered
to
client
overcoming
latency
14
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
15. DIFFERENTIATED
APPROACH
:
GPU
CLOUD
ARTIFICIAL
INTELLIGENCE
LEADS
TO
INTELLIGENT
VISUALIZATIONS®
" Pasern
RecogniDon
Using
ArDficial
Neural
Network
" HeurisDc
Search
Using
GeneDc
Algorithm
CPU
:
500s
GPU
:
10s
15K
Paserns
" Uses:
" Computer
Aided
Diagnosis
through
IntuiDve
VisualizaDons
" Cancer
or
Tumor
DetecDon
" SegmenDng
Body
Parts
" Intelligent
VisualizaDon®
R&D
ParDally
Funded
by
NaDonal
Science
FoundaDon
15
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November
22,
2013
|
CONFIDENTIAL
GPU
is
3000x
over
CPU
16. IP
SUMMARY
:
SUPERCOMPUTING
CLOUD
COMPARISON
Legacy
PACS
ConvenMonal
Cloud
KJAYA’s
SupercompuMng
Cloud
PlaVorm
Transmits
raw
scans
to
end
users
Streams
visualizaDon
on
demand
Compromises
raw
scan
for
faster
transmission
•
Not
fit
for
diagnosis
•
Computer
Aided
Diagnosis
(CAD)
inaccuracy
HD
quality
without
transmiqng
raw
scan
•
FDA
510K
cleared
primary
diagnosDc
use
•
ArDficial
Intelligence
CAD
on
gaming
technology
Storage
servers
cannot
manipulate
or
analyze
large
data
–
not
scalable
Graphics
processors
for
large
scan
manipulaDon
and
analyDcs
Powerful
PC
workstaDon
to
run
clinical
app
Clinical
apps
run
on
any
device
CAD
lack
breadth
of
data
and
processing
power
CAD
on
vast
historical
and
powerful
processors
using
arDficial
intelligence
algorithms
on
GPU
Tools
limited
by
vendor
capability
Flexible
toolkit
>
App
store
for
medical
imaging
No
barriers
to
entry
Filed
patents
since
2009
16
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
17. IP
:
PATENT
PENDING
PLATFORM
PATENT
APPLICATIONS
I. Secure
Cloud
SupercompuMng
based
Medical
Imaging
System
PCT/US2010/036355
for
“Method
and
System
for
Fast
Access
to
Advanced
VisualizaDon
of
Medical
Scans
Using
a
Dedicated
Web
Portal”
II. Hybrid
Cloud
for
Medical
Imaging
61/514,295
for
“Method
and
System
for
Fast
Access
to
Advanced
VisualizaDon
of
Medical
Scans
Using
Hybrid
Local
and
Dedicated
Web
Portal”
III. A
Scalable
Architecture
to
handle
large
amounts
of
data
and
users
11/672,581
for
"Method
and
System
for
Processing
a
Volume
VisualizaDon
Dataset
IV. ArMficial
Intelligence
on
GPU
for
3D
and
Computer
Aided
DetecMon
PCT/US11/45047
for
“AdapDve
VisualizaDon
for
Direct
Physician
Use”
V. Patent
Firm:
DeLio
&
Peterson,
New
Haven,
CT
(near
Yale
University)
17
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November
22,
2013
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CONFIDENTIAL
18. COMPETITIVE
LANDSCAPE
PACS
RIS
Intelligent
VisualizaDons®
(AI)
3D
on
any
PC
4D
on
any
PC
Image
Sharing
Archive
&
Disaster
Recovery
DiagnosDc
Quality
over
Internet
FDA
Cleared
PredicDve
Streaming
(not
downloading)
MulD
data
center
SupercompuDng
plalorm
.
KJAYA
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
Y
CareStream
Y
Y
N
N
N
?
Y
N
Y
N
Y
N
TeraRecon*1
N
N
N
Y
N
N
N
?
Y
N
N
N
Shina*1
on
Amazon
Cloud
N
N
N
Y
N
N
N
N
Y
N
Y
N
vRAD
Y
N
N
N
N
N
Y
N
Y
N
Y
N
DICOM
Grid
Y
N
N
N
N
Y
Y
N
N
N
N
N
LifeImage*1
N
N
N
N
N
Y
N
N
N
N
N
N
AccelaRad
Y
N
N
N
N
Y
N
N
N
N
N
N
InsiteOne*1
N
N
N
N
N
N
Y
N
N
N
Y
N
BRIT
Y
Y
N
N
N
N
N
N
Y
N
N
N
MedWeb
Y
Y
N
N
N
N
N
N
Y
N
N
N
secureRAD
Y
N
N
N
N
N
?
N
?
N
N
N
ScImage
Y
N
N
N
N
N
?
N
?
N
N
N
NCS
Y
Y
N
N
N
N
?
N
Y
N
N
N
18
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TITLE
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November
22,
2013
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CONFIDENTIAL
19. INDUSTRY
INSIDER
RECOGNITIONS
"Most
cloud-‐compuDng
services
don’t
offer
diagnosDc-‐quality
images,
and
the
ones
that
do
typically
feature
lag
Dme,
slowing
the
process.
The
ability
to
quickly
process
and
transmit
diagnosDc-‐level
images
sets
KJAYA
apart
in
this
regard."
Christopher
Gaerig,
Imaging
Economics
“Today’s
medical
environment
demands
efficient,
cost-‐effecDve
workflow
and
VoXcell
delivers
the
tools
that
can
empower
faster
and
more
accurate
diagnosis
within
an
extremely
affordable
fee
structure."
Frost
&
Sullivan
“These
are
ambiDous
companies,
with
highly
innovaDve
products
and
business
development
strategies
that
will
enable
them
to
carve
out
a
place
in
global
markets....”
KJAYA’s
INVESTOR:
Enterprise
Ireland
19
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November
22,
2013
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CONFIDENTIAL
21. CLUSTER
COMPONENTS
BIG
DATA
CLUSTER
A
Node
24
TB
Storage
5
TFLOPS
AMD
GPU
2
CPU
Up
to
192GB
Memory
90,000
IOPS
Two
Nodes
48
TB
Storage
2
AMD
GPU
(10,000
GFLOPS)
4
CPU
(360
GFLOPS)
Up
to
384GB
Memory
180,000
IOPS
21
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TITLE
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November
22,
2013
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CONFIDENTIAL
24. ARCHITECTURAL
COMPARISON
" CPU+GPU=APU
CPU
VERSUS
HYBRID
CLOUD
ConvenDonal
DiagnosMc
KJAYA’s
VoXcell®
Cloud
Non-‐
DiagnosMc
" Not
on
" On
Access
demand
demand
DiagnosMc
" On
demand
Cloud
Cloud
CPU
Process
CPU
GPU
Data
RelaDonal
Database
Storage
24
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TITLE
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November
22,
2013
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CONFIDENTIAL
Big
Data
Clusters
25. WHY
APU?
REDUCED
POWER
CONSUMPTION
CPU
GPU
" 5A
" Mostly
dissipated
as
heat
! VS
25
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PRESENTATION
TITLE
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November
22,
2013
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CONFIDENTIAL
26. WHY
APU?
MANAGE
EVER-‐EXPANDING
VOLUMES
OF
MEDICAL
IMAGING
DATA
26
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PRESENTATION
TITLE
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November
22,
2013
|
CONFIDENTIAL
27. WHY
APU
WITH
HSA?
HETEROGENEOUS
UNIFORM
MEMORY
ACCESS
(HUMA)
27
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TITLE
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November
22,
2013
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CONFIDENTIAL
28. HUMA
USAGE
IN
GPU
BASED
VOLUME
RENDERING
PRE-‐COMPUTED
CLASSIFICATION
VOLUME
" Intensity
28
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PRESENTATION
TITLE
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November
22,
2013
|
CONFIDENTIAL
" {Bone,
Tissue,
Air}
29. GPU
BASED
MULTIDIMENSIONAL
TRANFER
FUNCTION
VOLUME
RENDERING
USING
PRE-‐COMPUTED
CLASSIFICATION
VOLUME
29
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PRESENTATION
TITLE
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November
22,
2013
|
CONFIDENTIAL