The document discusses NVIDIA's Compute Unified Device Architecture (CUDA). It provides an overview of CUDA, including the CUDA programming model, memory model, and application programming interface. It also presents a simple example of using CUDA for matrix multiplication, with one thread calculating one element of the result matrix and data transferred between host and device memory.
Unikraft: Fast, Specialized Unikernels the Easy WayScyllaDB
P99 CONF
Unikernels are famous for providing excellent performance in terms of boot times, throughput and memory consumption, to name a few metrics. However, they are infamous for making it hard and extremely time consuming to extract such performance, and for needing significant engineering effort in order to port applications to them. We introduce Unikraft, a novel micro-library OS that (1) fully modularizes OS primitives so that it is easy to customize the unikernel and include only relevant components and (2) exposes a set of composable, performance-oriented APIs in order to make it easy for developers to obtain high performance.
Our evaluation using off-the-shelf applications such as nginx, SQLite, and Redis shows that running them on Unikraft results in a 1.7x-2.7x performance improvement compared to Linux guests. In addition, Unikraft images for these apps are around 1MB, require less than 10MB of RAM to run, and boot in around 1ms on top of the VMM time (total boot time 3ms-40ms). Unikraft is a Linux Foundation open source project and can be found at www.unikraft.org.
Taking Killzone Shadow Fall Image Quality Into The Next GenerationGuerrilla
This talk focuses on the technical side of Killzone Shadow Fall, the platform exclusive launch title for PlayStation 4.
We present the details of several new techniques that were developed in the quest for next generation image quality, and the talk uses key locations from the game as examples. We discuss interesting aspects of the new content pipeline, next-gen lighting engine, usage of indirect lighting and various shadow rendering optimizations. We also describe the details of volumetric lighting, the real-time reflections system, and the new anti-aliasing solution, and include some details about the image-quality driven streaming system. A common, very important, theme of the talk is the temporal coherency and how it was utilized to reduce aliasing, and improve the rendering quality and image stability above the baseline 1080p resolution seen in other games.
In this presentation we will provide in-depth knowledge about the Unity runtime. The first part will focus on memory and how to deal with fragmentation and garbage collection. The second part on performance profiling and optimizations. Finally, there will be an overview of debugging and profiling improvements in the newly announced Unity 5.0.
Precomputed Voxelized-Shadows for Large-scale Scene and Many lightsSeongdae Kim
The document describes the process of building a voxel directional-occlusion graph (voxel DAG) from a shadow map captured on the GPU. It involves capturing the shadow map on the GPU and transmitting it to system memory, then computing minimum and maximum depth values at each mip level. A voxel DAG is constructed from the shadow data to represent lit and shadowed regions of the scene. Pseudocode is provided for building the root and subnodes of the voxel DAG in C#.
Screen Space Decals in Warhammer 40,000: Space MarinePope Kim
My Siggraph 2012 presentation slides on Screen Space Decals in Warhammer 40,000: Space Marine.
SSD is similar to Deferred Decals, so I focused more on the problems we had and how we solved(or avoided) them
This document provides an introduction to OpenCL, including:
- An overview of the OpenCL model and how work is distributed across CPUs and GPUs.
- A demonstration of an N-body simulation and how it can be parallelized with OpenCL.
- Details on OpenCL concepts like platforms, devices, memory model, and how applications are organized with host code and kernels.
Refresh what you know about AssetDatabase.Refresh()- Unite Copenhagen 2019Unity Technologies
The AssetDatabase has been rewritten. The more you know about how this API works, the stronger your code will be. This information can guide your decision-making for your own Asset Management strategies. For example, you do not need to reimport assets when you jump between platforms. In this session, you'll gain a deeper understanding of importing modified assets and tracking dependencies to improve your workflow and iteration time significantly.
Speaker: Javier Abud Chavez- Unity
Watch the session on Youtube: https://youtu.be/S2P9n5U9xVw
The document discusses NVIDIA's Compute Unified Device Architecture (CUDA). It provides an overview of CUDA, including the CUDA programming model, memory model, and application programming interface. It also presents a simple example of using CUDA for matrix multiplication, with one thread calculating one element of the result matrix and data transferred between host and device memory.
Unikraft: Fast, Specialized Unikernels the Easy WayScyllaDB
P99 CONF
Unikernels are famous for providing excellent performance in terms of boot times, throughput and memory consumption, to name a few metrics. However, they are infamous for making it hard and extremely time consuming to extract such performance, and for needing significant engineering effort in order to port applications to them. We introduce Unikraft, a novel micro-library OS that (1) fully modularizes OS primitives so that it is easy to customize the unikernel and include only relevant components and (2) exposes a set of composable, performance-oriented APIs in order to make it easy for developers to obtain high performance.
Our evaluation using off-the-shelf applications such as nginx, SQLite, and Redis shows that running them on Unikraft results in a 1.7x-2.7x performance improvement compared to Linux guests. In addition, Unikraft images for these apps are around 1MB, require less than 10MB of RAM to run, and boot in around 1ms on top of the VMM time (total boot time 3ms-40ms). Unikraft is a Linux Foundation open source project and can be found at www.unikraft.org.
Taking Killzone Shadow Fall Image Quality Into The Next GenerationGuerrilla
This talk focuses on the technical side of Killzone Shadow Fall, the platform exclusive launch title for PlayStation 4.
We present the details of several new techniques that were developed in the quest for next generation image quality, and the talk uses key locations from the game as examples. We discuss interesting aspects of the new content pipeline, next-gen lighting engine, usage of indirect lighting and various shadow rendering optimizations. We also describe the details of volumetric lighting, the real-time reflections system, and the new anti-aliasing solution, and include some details about the image-quality driven streaming system. A common, very important, theme of the talk is the temporal coherency and how it was utilized to reduce aliasing, and improve the rendering quality and image stability above the baseline 1080p resolution seen in other games.
In this presentation we will provide in-depth knowledge about the Unity runtime. The first part will focus on memory and how to deal with fragmentation and garbage collection. The second part on performance profiling and optimizations. Finally, there will be an overview of debugging and profiling improvements in the newly announced Unity 5.0.
Precomputed Voxelized-Shadows for Large-scale Scene and Many lightsSeongdae Kim
The document describes the process of building a voxel directional-occlusion graph (voxel DAG) from a shadow map captured on the GPU. It involves capturing the shadow map on the GPU and transmitting it to system memory, then computing minimum and maximum depth values at each mip level. A voxel DAG is constructed from the shadow data to represent lit and shadowed regions of the scene. Pseudocode is provided for building the root and subnodes of the voxel DAG in C#.
Screen Space Decals in Warhammer 40,000: Space MarinePope Kim
My Siggraph 2012 presentation slides on Screen Space Decals in Warhammer 40,000: Space Marine.
SSD is similar to Deferred Decals, so I focused more on the problems we had and how we solved(or avoided) them
This document provides an introduction to OpenCL, including:
- An overview of the OpenCL model and how work is distributed across CPUs and GPUs.
- A demonstration of an N-body simulation and how it can be parallelized with OpenCL.
- Details on OpenCL concepts like platforms, devices, memory model, and how applications are organized with host code and kernels.
Refresh what you know about AssetDatabase.Refresh()- Unite Copenhagen 2019Unity Technologies
The AssetDatabase has been rewritten. The more you know about how this API works, the stronger your code will be. This information can guide your decision-making for your own Asset Management strategies. For example, you do not need to reimport assets when you jump between platforms. In this session, you'll gain a deeper understanding of importing modified assets and tracking dependencies to improve your workflow and iteration time significantly.
Speaker: Javier Abud Chavez- Unity
Watch the session on Youtube: https://youtu.be/S2P9n5U9xVw
Talk by Graham Wihlidal (Frostbite Labs) at GDC 2017.
Checkerboard rendering is a relatively new technique, popularized recently by the introduction of the PlayStation 4 Pro. Many modern game engines are adding support for it right now, and in this talk, Graham will present an in-depth look at the new implementation in Frostbite, which is used in shipping titles like 'Battlefield 1' and 'Mass Effect Andromeda'. Despite being conceptually simple, checkerboard rendering requires a deep integration into the post-processing chain, in particular temporal anti-aliasing, dynamic resolution scaling, and poses various challenges to existing effects. This presentation will cover the basics of checkerboard rendering, explain the impact on a game engine that powers a wide range of titles, and provide a detailed look at how the current implementation in Frostbite works, including topics like object id, alpha unrolling, gradient adjust, and a highly efficient depth resolve.
This document summarizes a presentation about hair rendering in the video game Tomb Raider. It discusses the motivation for improving Lara Croft's hair, the TressFX technology used, and the multi-studio collaboration between AMD, Crystal Dynamics, Nixxes, Confetti, and Square Enix. Key aspects covered include hair authoring, simulation of hair movement through physics, rendering techniques like geometry expansion, anti-aliasing, lighting and shadows, and use of per-pixel linked lists. Performance numbers are provided for different passes on an AMD Radeon HD 7970 graphics card.
Gstreamer plugin development involves creating elements, plugins, and pads. Elements are the core components that process media streams. Plugins contain implementations of elements and are loaded on demand. Pads negotiate media flow between elements and ensure type compatibility. The chain function processes incoming buffers and passes them downstream. A simple pass-through filter would implement chain to push incoming buffers to the output pad without modification.
Graphics Gems from CryENGINE 3 (Siggraph 2013)Tiago Sousa
This lecture covers rendering topics related to Crytek’s latest engine iteration, the technology which powers titles such as Ryse, Warface, and Crysis 3. Among covered topics, Sousa presented SMAA 1TX: an update featuring a robust and simple temporal antialising component; performant and physically-plausible camera related post-processing techniques such as motion blur and depth of field were also covered.
Integration of neutron, nova and designate how to use it and how to configur...Miguel Lavalle
This document discusses integrating Neutron, Nova, and Designate for DNS resolution and configuration. It provides three use cases: 1) floating IPs are published with associated port DNS attributes, 2) floating IPs are published directly in an external DNS service, and 3) ports are published directly in an external DNS service. It also covers configuring Neutron's internal DNS resolution, integrating with an external DNS service like Designate, and potential performance impacts of publishing ports directly to external DNS.
This talk presents the approach Frostbite took to add support for HDR displays. It will summarize Frostbite's previous post processing pipeline and what the issues were. Attendees will learn the decisions made to fix these issues, improve the color grading workflow and support high quality HDR and SDR output. This session will detail the display mapping used to implement the"grade once, output many" approach to targeting any display and why an ad-hoc approach as opposed to filmic tone mapping was chosen. Frostbite retained 3D LUT-based grading flexibility and the accuracy differences of computing these in decorrelated color spaces will be shown. This session will also include the main issues found on early adopter games, differences between HDR standards, optimizations to achieve performance parity with the legacy path and why supporting HDR can also improve the SDR version.
Takeaway
Attendees will learn how and why Frostbite chose to support High Dynamic Range [HDR] displays. They will understand the issues faced and how these were resolved. This talk will be useful for those still to support HDR and provide discussion points for those who already do.
Intended Audience
The intended audience is primarily rendering engineers, technical artists and artists; specifically those who focus on grading and lighting and those interested in HDR displays. Ideally attendees will be familiar with color grading and tonemapping.
Developing and optimizing a procedural game: The Elder Scrolls Blades- Unite ...Unity Technologies
The Elder Scrolls Blades strove to produce high-quality visuals on modern mobile devices. This talk will describe the challenges of achieving that level of quality in procedurally generated 3D environments.
Speakers:
Simon-Pierre Thibault - Bethesda Game Studios
Sergei Savchenko - Bethesda Game Studios
Watch the session here: https://youtu.be/KbxiGH6igBk
Talk by Yuriy O’Donnell at GDC 2017.
This talk describes how Frostbite handles rendering architecture challenges that come with having to support a wide variety of games on a single engine. Yuriy describes their new rendering abstraction design, which is based on a graph of all render passes and resources. This approach allows implementation of rendering features in a decoupled and modular way, while still maintaining efficiency.
A graph of all rendering operations for the entire frame is a useful abstraction. The industry can move away from “immediate mode” DX11 style APIs to a higher level system that allows simpler code and efficient GPU utilization. Attendees will learn how it worked out for Frostbite.
The document discusses screen space reflections implemented in the game The Surge. It describes using screen space ray marching against the depth buffer to find reflection points, convolving the scene to accumulate multiple bounces, and using asynchronous compute to overlap rendering passes and improve performance. Key techniques included interleaved rendering, temporal reprojection, and using local data storage. Performance gains were achieved through optimizations like lower resolution rendering and computing mip chains in-place.
How the Universal Render Pipeline unlocks games for you - Unite Copenhagen 2019Unity Technologies
Learn how the Boat Attack demo was created using the Universal Render Pipeline. These slides offer an in-depth look at the features used in the demo, including Shader Graph, Custom Render Passes, Camera Callback, and more.
Speaker:
Andre McGrail - Unity Technologies
Watch the session on YouTube: https://youtu.be/ZPQdm1T7aRs
CryEngine 3 uses a deferred lighting approach that generates lighting information in screen space textures for efficient rendering of complex scenes on consoles and PC. Key features include storing normals, depth, and material properties in G-buffers, accumulating light contributions from multiple light types into textures, and supporting techniques like image-based lighting, shadow mapping, and real-time global illumination. Deferred rendering helps address shader combination issues and provides more predictable performance.
The document discusses light pre-pass (LPP) rendering techniques for deferred shading. LPP involves splitting rendering into a geometry pass to store surface properties, a lighting pass to store lit scene data in a light buffer, and a final pass to combine the information. The document describes optimizations for LPP on various hardware, including techniques for efficient light culling and storing data. It also discusses approaches for implementing multisample anti-aliasing with LPP.
Apresentação da ferramenta de Esteganografia JPHSFatinha de Sousa
O documento apresenta a ferramenta de esteganografia JPHS, que esconde arquivos dentro de imagens JPEG usando criptografia. O programa JPHide esconde arquivos após criptografá-los com a senha do usuário, enquanto o JPSeek recupera os arquivos ocultos ao inserir a mesma senha. Passos-chave incluem adicionar uma imagem JPEG anfitriã, escolher o arquivo a esconder, inseri-lo na imagem e salvá-la com o arquivo agora oculto.
Rendering AAA-Quality Characters of Project A1Ki Hyunwoo
The document discusses rendering techniques for high quality characters in an unannounced game project called A1. It covers skin rendering using subsurface scattering with multiple scattering approximations. It also covers hair rendering using ordered independent transparency with a linked list approach integrated into UE4, as well as a physically based shading model for hair. Future work discussed includes improvements to subsurface scattering, lighting, and shadowing for transparent and translucent materials.
eBPF is one of the key technologies nowadays. There are several existing technologies in network or observability fields but not much in storage space. This presentation tells my research story and tries to define some of the possibilities of the technology.
In this tutorial, you will learn the basics of scripting in Unity by:
- Creating a new script component and adding it to a GameObject
- Exploring the default script structure and functions like Start and Update
- Adding a variable to the script and editing its value in the Inspector
- Using Debug.Log to output messages to the Console
- Changing a property of a GameObject by editing values in the script
(DVO312) Sony: Building At-Scale Services with AWS Elastic BeanstalkAmazon Web Services
Learn about Sony's efforts to build a cloud-native authentication and profile management platform on AWS. Sony engineers demonstrate how they used AWS Elastic Beanstalk (Elastic Beanstalk) to deploy, manage, and scale their applications. They also describe how they use AWS CloudFormation for resource provisioning, Amazon DynamoDB for the main database, and AWS Lambda and Amazon Redshift for log handling and analysis. This discussion focuses on best practices, security considerations, tradeoffs, and final architecture and implementation. By the end of the session, you will clearly understand how to use Elastic Beanstalk as a platform to quickly and easily build at-scale web application on AWS, and how to use Elastic Beanstalk with other AWS services to build cloud-native applications.
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Studies have shown that meditating for just 10-20 minutes per day can have significant positive impacts on both mental and physical health over time.
PyCUDA provides a Python interface to CUDA that allows developers to write CUDA kernels in Python and execute them on NVIDIA GPUs. The example loads random data onto the GPU, defines a simple element-wise multiplication kernel in Python, compiles and runs the kernel on the GPU to multiply the arrays in parallel, and verifies the result matches multiplying the arrays on the CPU. PyCUDA handles memory transfers between CPU and GPU and provides tools for kernel definition, compilation and execution that abstract away many low-level CUDA API details.
The document provides an overview of GPU computing and CUDA programming. It discusses how GPUs enable massively parallel and affordable computing through their manycore architecture. The CUDA programming model allows developers to accelerate applications by launching parallel kernels on the GPU from their existing C/C++ code. Kernels contain many concurrent threads that execute the same code on different data. CUDA features a memory hierarchy and runtime for managing GPU memory and launching kernels. Overall, the document introduces GPU and CUDA concepts for general-purpose parallel programming on NVIDIA GPUs.
Talk by Graham Wihlidal (Frostbite Labs) at GDC 2017.
Checkerboard rendering is a relatively new technique, popularized recently by the introduction of the PlayStation 4 Pro. Many modern game engines are adding support for it right now, and in this talk, Graham will present an in-depth look at the new implementation in Frostbite, which is used in shipping titles like 'Battlefield 1' and 'Mass Effect Andromeda'. Despite being conceptually simple, checkerboard rendering requires a deep integration into the post-processing chain, in particular temporal anti-aliasing, dynamic resolution scaling, and poses various challenges to existing effects. This presentation will cover the basics of checkerboard rendering, explain the impact on a game engine that powers a wide range of titles, and provide a detailed look at how the current implementation in Frostbite works, including topics like object id, alpha unrolling, gradient adjust, and a highly efficient depth resolve.
This document summarizes a presentation about hair rendering in the video game Tomb Raider. It discusses the motivation for improving Lara Croft's hair, the TressFX technology used, and the multi-studio collaboration between AMD, Crystal Dynamics, Nixxes, Confetti, and Square Enix. Key aspects covered include hair authoring, simulation of hair movement through physics, rendering techniques like geometry expansion, anti-aliasing, lighting and shadows, and use of per-pixel linked lists. Performance numbers are provided for different passes on an AMD Radeon HD 7970 graphics card.
Gstreamer plugin development involves creating elements, plugins, and pads. Elements are the core components that process media streams. Plugins contain implementations of elements and are loaded on demand. Pads negotiate media flow between elements and ensure type compatibility. The chain function processes incoming buffers and passes them downstream. A simple pass-through filter would implement chain to push incoming buffers to the output pad without modification.
Graphics Gems from CryENGINE 3 (Siggraph 2013)Tiago Sousa
This lecture covers rendering topics related to Crytek’s latest engine iteration, the technology which powers titles such as Ryse, Warface, and Crysis 3. Among covered topics, Sousa presented SMAA 1TX: an update featuring a robust and simple temporal antialising component; performant and physically-plausible camera related post-processing techniques such as motion blur and depth of field were also covered.
Integration of neutron, nova and designate how to use it and how to configur...Miguel Lavalle
This document discusses integrating Neutron, Nova, and Designate for DNS resolution and configuration. It provides three use cases: 1) floating IPs are published with associated port DNS attributes, 2) floating IPs are published directly in an external DNS service, and 3) ports are published directly in an external DNS service. It also covers configuring Neutron's internal DNS resolution, integrating with an external DNS service like Designate, and potential performance impacts of publishing ports directly to external DNS.
This talk presents the approach Frostbite took to add support for HDR displays. It will summarize Frostbite's previous post processing pipeline and what the issues were. Attendees will learn the decisions made to fix these issues, improve the color grading workflow and support high quality HDR and SDR output. This session will detail the display mapping used to implement the"grade once, output many" approach to targeting any display and why an ad-hoc approach as opposed to filmic tone mapping was chosen. Frostbite retained 3D LUT-based grading flexibility and the accuracy differences of computing these in decorrelated color spaces will be shown. This session will also include the main issues found on early adopter games, differences between HDR standards, optimizations to achieve performance parity with the legacy path and why supporting HDR can also improve the SDR version.
Takeaway
Attendees will learn how and why Frostbite chose to support High Dynamic Range [HDR] displays. They will understand the issues faced and how these were resolved. This talk will be useful for those still to support HDR and provide discussion points for those who already do.
Intended Audience
The intended audience is primarily rendering engineers, technical artists and artists; specifically those who focus on grading and lighting and those interested in HDR displays. Ideally attendees will be familiar with color grading and tonemapping.
Developing and optimizing a procedural game: The Elder Scrolls Blades- Unite ...Unity Technologies
The Elder Scrolls Blades strove to produce high-quality visuals on modern mobile devices. This talk will describe the challenges of achieving that level of quality in procedurally generated 3D environments.
Speakers:
Simon-Pierre Thibault - Bethesda Game Studios
Sergei Savchenko - Bethesda Game Studios
Watch the session here: https://youtu.be/KbxiGH6igBk
Talk by Yuriy O’Donnell at GDC 2017.
This talk describes how Frostbite handles rendering architecture challenges that come with having to support a wide variety of games on a single engine. Yuriy describes their new rendering abstraction design, which is based on a graph of all render passes and resources. This approach allows implementation of rendering features in a decoupled and modular way, while still maintaining efficiency.
A graph of all rendering operations for the entire frame is a useful abstraction. The industry can move away from “immediate mode” DX11 style APIs to a higher level system that allows simpler code and efficient GPU utilization. Attendees will learn how it worked out for Frostbite.
The document discusses screen space reflections implemented in the game The Surge. It describes using screen space ray marching against the depth buffer to find reflection points, convolving the scene to accumulate multiple bounces, and using asynchronous compute to overlap rendering passes and improve performance. Key techniques included interleaved rendering, temporal reprojection, and using local data storage. Performance gains were achieved through optimizations like lower resolution rendering and computing mip chains in-place.
How the Universal Render Pipeline unlocks games for you - Unite Copenhagen 2019Unity Technologies
Learn how the Boat Attack demo was created using the Universal Render Pipeline. These slides offer an in-depth look at the features used in the demo, including Shader Graph, Custom Render Passes, Camera Callback, and more.
Speaker:
Andre McGrail - Unity Technologies
Watch the session on YouTube: https://youtu.be/ZPQdm1T7aRs
CryEngine 3 uses a deferred lighting approach that generates lighting information in screen space textures for efficient rendering of complex scenes on consoles and PC. Key features include storing normals, depth, and material properties in G-buffers, accumulating light contributions from multiple light types into textures, and supporting techniques like image-based lighting, shadow mapping, and real-time global illumination. Deferred rendering helps address shader combination issues and provides more predictable performance.
The document discusses light pre-pass (LPP) rendering techniques for deferred shading. LPP involves splitting rendering into a geometry pass to store surface properties, a lighting pass to store lit scene data in a light buffer, and a final pass to combine the information. The document describes optimizations for LPP on various hardware, including techniques for efficient light culling and storing data. It also discusses approaches for implementing multisample anti-aliasing with LPP.
Apresentação da ferramenta de Esteganografia JPHSFatinha de Sousa
O documento apresenta a ferramenta de esteganografia JPHS, que esconde arquivos dentro de imagens JPEG usando criptografia. O programa JPHide esconde arquivos após criptografá-los com a senha do usuário, enquanto o JPSeek recupera os arquivos ocultos ao inserir a mesma senha. Passos-chave incluem adicionar uma imagem JPEG anfitriã, escolher o arquivo a esconder, inseri-lo na imagem e salvá-la com o arquivo agora oculto.
Rendering AAA-Quality Characters of Project A1Ki Hyunwoo
The document discusses rendering techniques for high quality characters in an unannounced game project called A1. It covers skin rendering using subsurface scattering with multiple scattering approximations. It also covers hair rendering using ordered independent transparency with a linked list approach integrated into UE4, as well as a physically based shading model for hair. Future work discussed includes improvements to subsurface scattering, lighting, and shadowing for transparent and translucent materials.
eBPF is one of the key technologies nowadays. There are several existing technologies in network or observability fields but not much in storage space. This presentation tells my research story and tries to define some of the possibilities of the technology.
In this tutorial, you will learn the basics of scripting in Unity by:
- Creating a new script component and adding it to a GameObject
- Exploring the default script structure and functions like Start and Update
- Adding a variable to the script and editing its value in the Inspector
- Using Debug.Log to output messages to the Console
- Changing a property of a GameObject by editing values in the script
(DVO312) Sony: Building At-Scale Services with AWS Elastic BeanstalkAmazon Web Services
Learn about Sony's efforts to build a cloud-native authentication and profile management platform on AWS. Sony engineers demonstrate how they used AWS Elastic Beanstalk (Elastic Beanstalk) to deploy, manage, and scale their applications. They also describe how they use AWS CloudFormation for resource provisioning, Amazon DynamoDB for the main database, and AWS Lambda and Amazon Redshift for log handling and analysis. This discussion focuses on best practices, security considerations, tradeoffs, and final architecture and implementation. By the end of the session, you will clearly understand how to use Elastic Beanstalk as a platform to quickly and easily build at-scale web application on AWS, and how to use Elastic Beanstalk with other AWS services to build cloud-native applications.
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Studies have shown that meditating for just 10-20 minutes per day can have significant positive impacts on both mental and physical health over time.
PyCUDA provides a Python interface to CUDA that allows developers to write CUDA kernels in Python and execute them on NVIDIA GPUs. The example loads random data onto the GPU, defines a simple element-wise multiplication kernel in Python, compiles and runs the kernel on the GPU to multiply the arrays in parallel, and verifies the result matches multiplying the arrays on the CPU. PyCUDA handles memory transfers between CPU and GPU and provides tools for kernel definition, compilation and execution that abstract away many low-level CUDA API details.
The document provides an overview of GPU computing and CUDA programming. It discusses how GPUs enable massively parallel and affordable computing through their manycore architecture. The CUDA programming model allows developers to accelerate applications by launching parallel kernels on the GPU from their existing C/C++ code. Kernels contain many concurrent threads that execute the same code on different data. CUDA features a memory hierarchy and runtime for managing GPU memory and launching kernels. Overall, the document introduces GPU and CUDA concepts for general-purpose parallel programming on NVIDIA GPUs.
This document provides an overview of CUDA (Compute Unified Device Architecture), NVIDIA's parallel computing platform and programming model that allows software developers to leverage the parallel compute engines in NVIDIA GPUs. The document discusses key aspects of CUDA including: GPU hardware architecture with many scalar processors and concurrent threads; the CUDA programming model with host CPU code calling parallel kernels that execute across multiple GPU threads; memory hierarchies and data transfers between host and device memory; and programming basics like compiling with nvcc, allocating and copying data between host and device memory.
GPU, CUDA, OpenCL and OpenACC for Parallel ApplicationsMarcos Gonzalez
O documento discute GPUs, CUDA e OpenCL para aplicações paralelas. Aborda a evolução das GPUs, arquiteturas como Tesla, Fermi e Kepler, e frameworks como CUDA e OpenCL para programação em GPUs de forma paralela, incluindo organização de memória e execução de kernels.
Baidu World 2016 With NVIDIA CEO Jen-Hsun HuangNVIDIA
Jen-Hsun Huang, CEO of NVIDIA, gave a keynote speech at the 2016 Baidu World Conference. He discussed how NVIDIA GPUs have become the dominant platform for artificial intelligence research and deep learning. GPUs enabled breakthroughs like superhuman image recognition in 2012 and voice recognition in 2015. NVIDIA's Pascal GPU architecture provides a 65x speedup for deep learning compared to 4 years ago. Huang outlined NVIDIA's work in self-driving cars through its Drive PX platform and partnership with Baidu to apply AI to transportation and other domains.
A Platform for Accelerating Machine Learning ApplicationsNVIDIA Taiwan
Robert Sheen from HPE gave a presentation on machine learning applications and accelerating deep learning. He provided a quick introduction to neural networks, discussing their structure and how they are inspired by biological neurons. Deep learning requires high performance computing due to its computational intensity during training. Popular deep learning frameworks like CogX were also discussed, which provide tools and libraries to help build and optimize neural networks. Finally, several enterprise use cases for machine learning and deep learning were highlighted, such as in finance, healthcare, security, and geospatial applications.
Enabling Artificial Intelligence - Alison B. LowndesWithTheBest
This document discusses NVIDIA's deep learning technologies and platforms. It highlights NVIDIA's GPUs and deep learning software that accelerate major deep learning frameworks and power applications like self-driving cars, medical robotics, and natural language processing. It also introduces NVIDIA's deep learning supercomputer DGX-1 and embedded module Jetson TX1 for edge devices. The document promotes NVIDIA's deep learning events and career opportunities.
Evolution of Supermicro GPU Server SolutionNVIDIA Taiwan
Supermicro provides energy efficient server solutions optimized for GPU computing. Their portfolio includes 1U and 4U servers that support up to 10 GPUs, delivering the highest rack-level and node-level GPU density. Their new generation of solutions are optimized for machine learning applications using NVIDIA Pascal GPUs, with features like NVLink for high bandwidth GPU interconnect and direct low latency data access between GPUs. These solutions deliver the highest performance per watt for parallel workloads like machine learning training.
Introduction to multi gpu deep learning with DIGITS 2 - Mike WangPAPIs.io
This document introduces multi-GPU deep learning with DIGITS 2. It begins with an overview of deep learning and how GPUs are well-suited for deep learning tasks due to their parallel processing capabilities. It then discusses NVIDIA DIGITS, an interactive deep learning system that allows users to design neural networks, visualize activations, and manage training across multiple GPUs. The document concludes by discussing deep learning deployment workflows.
This document discusses NVIDIA's DGX-1 supercomputer and its applications for artificial intelligence and deep learning. It describes how the DGX-1 uses NVIDIA's Tesla P100 GPUs with NVLink connections to provide very high performance for deep learning workloads. It also discusses NVIDIA's software stack for deep learning including cuDNN, DIGITS, and Docker containers, which provide developers with tools for training and deploying neural networks. The document emphasizes how the DGX-1 and NVIDIA's GPUs are optimized for data center use through features like reliability, scalability, and management tools.
Nvidia Deep Learning Solutions - Alex SabatierSri Ambati
Alex Sabatier from Nvidia talks about the future of Deep Learning from an chipmaker perspective
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- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
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.
At CES 2016, we made a series of announcements highlighting our work to advance the biggest trends in the industry — self-driving cars, artificial intelligence and
virtual reality. The focus of our news was NVIDIA DRIVE, an end-to-end deep learning platform for self-driving cars.
The document discusses a community-based deep learning benchmark using an NVIDIA DGX-1 supercomputer. It announces that the benchmark will be set up by mid-March 2017 and interested participants should contact them. It also summarizes previous benchmarks conducted on different GPUs and frameworks, comparing efficiency when training various neural networks. Details are provided on benchmarks measuring minibatch efficiency for TensorFlow. Participants are directed to a blog post for more information.
At a press event kicking off CES 2016, we unveiled artificial intelligence technology that will let cars sense the world around them and pilot a safe route forward.
Dressed in his trademark black leather jacket, speaking to a crowd of some 400 automakers, media and analysts, NVIDIA CEO Jen-Hsun Huang revealed DRIVE PX 2, an automotive supercomputing platform that processes 24 trillion deep learning operations a second. That’s 10 times the performance of the first-generation DRIVE PX, now being used by more than 50 companies in the automotive world.
The new DRIVE PX 2 delivers 8 teraflops of processing power. It has the processing power of 150 MacBook Pros. And it’s the size of a lunchbox in contrast to other autonomous-driving technology being used today, which takes up the entire trunk of a mid-sized sedan.
“Self-driving cars will revolutionize society,” Huang said at the beginning of his talk. “And NVIDIA’s vision is to enable them.”
NVIDIA's Jetson platform provides an AI computing solution for applications at the edge by running deep neural networks on low-power modules like the Jetson TX1. The Jetson TX1 module has powerful GPU processing capable of over 1 teraflop/s while consuming under 10 watts, making it suitable for applications in areas like industrial automation, robotics, smart cities, and more. Developers can use the Jetpack SDK and resources like the Deep Learning Institute to train models on servers and deploy them to Jetson modules for running AI inference in end products at the edge.
[Harvard CS264] 05 - Advanced-level CUDA Programmingnpinto
The document discusses optimizations for memory and communication in massively parallel computing. It recommends caching data in faster shared memory to reduce loads and stores to global device memory. This can improve performance by avoiding non-coalesced global memory accesses. The document provides an example of coalescing writes for a matrix transpose by first loading data into shared memory and then writing columns of the tile to global memory in contiguous addresses.
IAP09 CUDA@MIT 6.963 - Lecture 01: GPU Computing using CUDA (David Luebke, NV...npinto
The document discusses parallel computing using GPUs and CUDA. It introduces CUDA as a parallel programming model that allows writing parallel code in a C/C++-like language that can execute efficiently on NVIDIA GPUs. It describes key CUDA abstractions like a hierarchy of threads organized into blocks, different memory spaces, and synchronization methods. It provides an example of implementing parallel reduction and discusses strategies for mapping algorithms to GPU architectures. The overall message is that CUDA makes massively parallel computing accessible using a familiar programming approach.
The document provides an introduction to GPU programming using CUDA. It outlines GPU and CPU architectures, the CUDA programming model involving threads, blocks and grids, and CUDA C language extensions. It also discusses compilation with NVCC, memory hierarchies, profiling code with Valgrind/Callgrind, and Amdahl's law in the context of parallelization. A simple CUDA program example is provided to demonstrate basic concepts like kernel launches and data transfers between host and device memory.
GPU computing provides a way to access the power of massively parallel graphics processing units (GPUs) for general purpose computing. GPUs contain over 100 processing cores and can achieve over 500 gigaflops of performance. The CUDA programming model allows programmers to leverage this parallelism by executing compute kernels on the GPU from their existing C/C++ applications. This approach democratizes parallel computing by making highly parallel systems accessible through inexpensive GPUs in personal computers and workstations. Researchers can now explore manycore architectures and parallel algorithms using GPUs as a platform.
1. CUDA provides a programming environment and APIs that allow developers to leverage GPUs for general purpose computing. The CUDA C API offers both a high-level runtime API and a lower-level driver API.
2. CUDA programs define kernels that execute many parallel threads on the GPU. Threads are organized into blocks that can cooperate through shared memory, and blocks are organized into grids.
3. The CUDA memory model includes a hierarchy from fast per-thread registers to slower shared, global, and host memories. This hierarchy allows threads within blocks to communicate efficiently through shared memory.
The document discusses Compute Unified Device Architecture (CUDA), which is a parallel computing platform and programming model created by Nvidia that allows software developers to use GPUs for general-purpose processing. It provides an overview of CUDA, including its execution model, implementation details, applications, and advantages/drawbacks. The document also covers CUDA programming, compiling CUDA code, CUDA architectures, and concludes that CUDA has brought significant innovations to high performance computing.
This document discusses the concept of threads. It defines a thread as the smallest sequence of programmed instructions that can be managed independently by an operating system scheduler. Threads allow for parallel computing and resource sharing. The benefits of threads include maintaining responsiveness, prioritizing tasks, and performing long operations without stopping other tasks. Threads can be user threads scheduled in user space or kernel threads scheduled across CPUs. Common threading models include user threads (N:1), kernel threads (1:1), and hybrid models (M:N). The document also discusses threading in C# and strategies for safely sharing data between threads to avoid issues like race conditions.
This document provides an outline of manycore GPU architectures and programming. It introduces GPU architectures, the GPGPU concept, and CUDA programming. It discusses the GPU execution model, CUDA programming model, and how to work with different memory types in CUDA like global, shared and constant memory. It also covers streams and concurrency, CUDA intrinsics and libraries, performance profiling and debugging. Finally, it mentions directive-based programming models like OpenACC and OpenMP.
C for Cuda - Small Introduction to GPU computingIPALab
In this talk, we are presenting a short introduction to CUDA and GPU computing to help anyone who reads it to get started with this technology.
At first, we are introducing the GPU from the hardware point of view: what is it? How is it built? Why use it for General Purposes (GPGPU)? How does it differ from the CPU?
The second part of the presentation is dealing with the software abstraction and the use of CUDA to implement parallel computing. The software architecture, the kernels and the different types of memories are tackled in this part.
Finally, and to illustrate what has been presented previously, examples of codes are given. These examples are also highlighting the issues that may occur while using parallel-computing.
The document provides an introduction and overview of parallel computing. It discusses parallel computing systems and parallel programming models like MPI and OpenMP. It covers theoretical concepts like Amdahl's law and practical limits of parallel computing related to load balancing and non-computational sections. Examples of parallel programming using MPI and OpenMP are also presented.
The Beagle Bone Black is a low-cost development platform that allows developers to boot Linux in under 10 seconds and get started on development quickly using just a USB cable. It has an ARM Cortex-A8 processor, 512MB RAM, and connectivity options like USB, Ethernet, HDMI. The Beagle Bone Black supports software like Angstrom Linux, Android, and Cloud9 IDE. It can be used for physical computing, robotics, and running programs like OpenCV for image analysis. Capes expansion boards can add functionality like motors, sensors, and cameras.
XPDDS17: Keynote: Shared Coprocessor Framework on ARM - Oleksandr Andrushchen...The Linux Foundation
With the grown interest in virtualization from big players around the world there are more and more companies choose ARM SoCs as their target platform for running server environments. It is also known that majority of such SoCs come with broad coprocessors available on the die, e.g. GPU, DSP, security etc. But at the moment the only way to speed up guests with these is either using a para-virtualized approach or making that HW dedicated to a specific guest.
Shared coprocessor framework for Xen aims to allow all guest OSes to benefit from this companion HW with ease while running unmodified software and/or firmware on guest side. You don’t need to worry about setting up IO ranges, interrupts, scheduling etc.: it is all covered, making support of new shared HW way faster.
As an example of the shared coprocessor framework usage a virtualized GPU will be shown.
- Exadata is not a traditional appliance but rather a "Database Machine" that requires specialized administration due to its unique hardware and software components.
- A single role, the Database Machine Administrator (DMA), combines the skills of database administration, system administration, storage administration, and network administration to manage Exadata.
- Exadata frames can contain multiple separate clusters to isolate workloads like development, testing, and production environments.
The document discusses ROM hacking of classic video games for fun and as an entry point to learning about exploitation. It provides an overview of concepts like low-end embedded system architectures, memory mapping, and debugging tools. A Nintendo Entertainment System is used as a case study. The presentation argues that ROM hacking skills can transfer to analyzing embedded systems and industrial control systems from an information security perspective. It encourages starting simple before moving to more complex targets.
Graphics processing unit or GPU (also occasionally called visual processing unit or VPU) is a specialized microprocessor that offloads and accelerates graphics rendering from the central (micro) processor. Modern GPUs are very efficient at manipulating computer graphics, and their highly parallel structure makes them more effective than general-purpose CPUs for a range of complex algorithms. In CPU, only a fraction of the chip does computations where as the GPU devotes more transistors to data processing.
GPGPU is a programming methodology based on modifying algorithms to run on existing GPU hardware for increased performance. Unfortunately, GPGPU programming is significantly more complex than traditional programming for several reasons.
This document summarizes a presentation on datacenter computing trends and problems. It discusses how cooling is a major source of energy inefficiency in datacenters. It also explains how servers are rarely fully utilized but operate least efficiently during common usage of 30% load. The document advocates for achieving better energy proportionality so servers can be more efficient during typical usage levels. It presents approaches like disaggregated memory and servers that break CPU-memory co-location to improve efficiency and consolidation.
This document discusses porting Android to new hardware. It covers components that need to be ported like the bootloader, Linux kernel, and hardware libraries. It also discusses getting the Android Open Source Project code, developing device drivers, customizing the user-space, and building the Android system. The goal is to provide guidance on porting each part of the Android software stack to new CPU architectures and hardware boards.
The document discusses various ways to optimize storage performance for virtual machines, including:
1) Provisioning virtual disks using different QEMU emulated devices like virtio-blk and configuring the IOThread option to improve performance.
2) Performing NUMA pinning to ensure virtual CPUs, memory and I/O threads are placed on the same NUMA node as the host storage device.
3) Configuring virtual machine options like using raw block devices instead of image files, enabling the IOThread, and tuning QEMU and image file parameters to improve I/O performance.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Nunit vs XUnit vs MSTest Differences Between These Unit Testing Frameworks.pdfflufftailshop
When it comes to unit testing in the .NET ecosystem, developers have a wide range of options available. Among the most popular choices are NUnit, XUnit, and MSTest. These unit testing frameworks provide essential tools and features to help ensure the quality and reliability of code. However, understanding the differences between these frameworks is crucial for selecting the most suitable one for your projects.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program