PT-4059, Bolt: A C++ Template Library for Heterogeneous Computing, by Ben SanderAMD Developer Central
Presentation PT-4059, Bolt: A C++ Template Library for Heterogeneous Computing, by Ben Sander, at the AMD Developer Summit (APU13) November 11-13, 2013.
MM-4104, Smart Sharpen using OpenCL in Adobe Photoshop CC – Challenges and Ac...AMD Developer Central
Presentation MM-4104, Smart Sharpen using OpenCL in Adobe Photoshop CC – Challenges and Achievements, by Joseph Hsieh at the AMD Developer Summit, November 11-13, 2013.
PT-4142, Porting and Optimizing OpenMP applications to APU using CAPS tools, ...AMD Developer Central
The document discusses porting and optimizing OpenMP applications to AMD APUs using CAPS tools. It provides an overview of CAPS Enterprise, which develops compilers and tools to help customers leverage the performance of multi-core and many-core processors. It then discusses CAPS' OpenACC and OpenMP compilers, which can generate code for AMD GPUs and APUs from directive-based programming models. The document demonstrates how the CAPS OpenMP compiler can analyze OpenMP applications and generate optimized code for execution on AMD APUs, showing speedups for the HydroC benchmark application.
PT-4053, Advanced OpenCL - Debugging and Profiling Using AMD CodeXL, by Uri S...AMD Developer Central
This document discusses debugging and profiling challenges with OpenCL and how AMD CodeXL addresses them. It provides an overview of CodeXL's debugging and profiling capabilities for OpenCL, including API-level debugging, kernel source debugging, profiling views for APIs, objects, and kernel variables, and integrated support in Visual Studio. Demo code is included to illustrate pinpointing OpenCL errors and optimizing work item loads.
MM-4092, Optimizing FFMPEG and Handbrake Using OpenCL and Other AMD HW Capabi...AMD Developer Central
This document discusses optimizing FFmpeg and Handbrake using OpenCL. It describes FFmpeg as a popular open-source multimedia software library used for recording, converting, and streaming audio and video. It was optimized to leverage heterogeneous computing by accelerating video decoding and encoding using hardware accelerators and accelerating video processing filters using the GPU. Specific filters were implemented in OpenCL for improved performance compared to CPU. Performance tests showed the accelerated FFmpeg approach achieved significantly higher frame rates than the original CPU-only FFmpeg.
PT-4052, Introduction to AMD Developer Tools, by Yaki Tebeka and Gordon SelleyAMD Developer Central
The document introduces AMD's developer tools strategy and CodeXL tool. It discusses how AMD is converging its CPU and GPU tools into a unified HSA Developer Tools Suite, with CodeXL being a key tool. CodeXL allows debugging, profiling, and analyzing applications across AMD CPUs, GPUs, and APUs in a "white box" view. It is available for Windows, Visual Studio, and Linux. The document then describes several CodeXL capabilities such as GPU debugging, CPU and GPU profiling, static kernel analysis, and what is new in CodeXL.
PT-4058, Measuring and Optimizing Performance of Cluster and Private Cloud Ap...AMD Developer Central
Presentation PT-4058, Measuring and Optimizing Performance of Cluster and Private Cloud Applications Using PPA , by Hui Huang, Zhaoqiang Zheng and Lihua Zhang at the AMD Developer Summit (APU13) November 11-13, 2013
AMD held a developer summit to share updates on their APU and GPU products. They discussed how computing demands are increasing for gaming, simulations and cloud applications. AMD's APUs combine CPU and GPU capabilities on a single chip. Their newest APU, codenamed "Kaveri", will feature heterogeneous system architecture capabilities. It will offer improved graphics and efficiency over previous APU designs. AMD also unveiled their new Radeon R9 290X GPU and discussed how both products will benefit from lower-level APIs like Mantle.
CE-4030, Optimizing Photo Editing Application with HSA Technology, by Stanley...AMD Developer Central
This document discusses optimizing a photo editing application called PhotoDirector to take advantage of AMD's heterogeneous system architecture (HSA). It describes how photo editing pipelines involve computationally intensive RAW processing that could benefit from GPU acceleration. HSA allows sharing memory between the CPU and GPU to reduce bottlenecks. Performance tests show the potential for a 2x speedup using coarse-grained shared virtual memory buffers over OpenCL. The document concludes that HSA has great potential to improve performance for parallelizable and memory-intensive tasks in photo editing applications.
CC-4006, Deliver Hardware Accelerated Applications Using RemoteFX vGPU with W...AMD Developer Central
Presentation CC-4006, Deliver Hardware Accelerated Applications Using RemoteFX vGPU with Windows Server, by Derrick Isoka at the AMD Developer Summit (APU13) November 11-13, 2013
CC-4001, Aparapi and HSA: Easing the developer path to APU/GPU accelerated Ja...AMD Developer Central
Presentation CC-4001, Aparapi and HSA: Easing the developer path to APU/GPU accelerated Java applications, by Gary Frost and Vignesh Ravi at the AMD Developer Summit (APU13) Nov. 11-13, 2013.
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.
The document discusses the specifications and architecture of the AMD Radeon R9-290X graphics processing unit (GPU). Some key points:
- The R9-290X contains 44 compute units with a total of 2816 stream processors. It has a 512-bit GDDR5 memory interface providing 320 GB/sec of memory bandwidth.
- The GPU uses AMD's Graphics Core Next (GCN) architecture. This includes improvements to geometry processing, new local data share memory operations, and enhanced media processing instructions.
- The GCN architecture includes compute units containing vector units and a local data store. Compute units provide computational power through 2816 stream processors.
- New features include support for flat
Keynote (Phil Rogers) - The Programmers Guide to Reaching for the Cloud - by ...AMD Developer Central
Keynote presentation, The Programmers Guide to Reaching for the Cloud, by Phil Rogers, AMD Corporate Fellow, AMD, at the AMD Developer Summit (APU13), Nov. 11-13, 2013.
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
The document discusses HSA compiler technology. It outlines the architecture of HSA compilers, which leverage the LLVM framework and generate the HSAIL intermediate representation. Performance is improved through optimizations in the high-level compiler and a thin finalizer. OpenCL 2.0 features like shared virtual memory and platform atomics will be supported. The first release of the OpenCL/HSA compiler is planned for Q2 2014.
Mantle is a new low-level graphics API from EA that aims to simplify advanced game development and improve performance. It provides developers with more control over the GPU for optimizations. Mantle exposes the true capabilities of modern graphics hardware in a way that is accessible to developers. This allows for innovations like improved multi-GPU support, explicit resource management, and asynchronous compute. Mantle promises benefits like reduced driver overhead, better multi-threading, and more flexibility to optimize for all GPUs. EA sees Mantle driving future Frostbite engine designs by enabling new rendering techniques and optimizations.
Mantle allows Battlefield 4 to significantly improve CPU and GPU performance compared to DirectX 11. The game utilizes Mantle's low-level access to optimize shader compilation, pipeline state management, asynchronous compute and memory handling. Multi-GPU rendering is supported through Alternate Frame Rendering where resources are duplicated and updated asynchronously across GPUs.
PT-4052, Introduction to AMD Developer Tools, by Yaki Tebeka and Gordon SelleyAMD Developer Central
The document introduces AMD's developer tools strategy and CodeXL tool. It discusses how AMD is converging its CPU and GPU tools into a unified HSA Developer Tools Suite, with CodeXL being a key tool. CodeXL allows debugging, profiling, and analyzing applications across AMD CPUs, GPUs, and APUs in a "white box" view. It is available for Windows, Visual Studio, and Linux. The document then describes several CodeXL capabilities such as GPU debugging, CPU and GPU profiling, static kernel analysis, and what is new in CodeXL.
PT-4058, Measuring and Optimizing Performance of Cluster and Private Cloud Ap...AMD Developer Central
Presentation PT-4058, Measuring and Optimizing Performance of Cluster and Private Cloud Applications Using PPA , by Hui Huang, Zhaoqiang Zheng and Lihua Zhang at the AMD Developer Summit (APU13) November 11-13, 2013
AMD held a developer summit to share updates on their APU and GPU products. They discussed how computing demands are increasing for gaming, simulations and cloud applications. AMD's APUs combine CPU and GPU capabilities on a single chip. Their newest APU, codenamed "Kaveri", will feature heterogeneous system architecture capabilities. It will offer improved graphics and efficiency over previous APU designs. AMD also unveiled their new Radeon R9 290X GPU and discussed how both products will benefit from lower-level APIs like Mantle.
CE-4030, Optimizing Photo Editing Application with HSA Technology, by Stanley...AMD Developer Central
This document discusses optimizing a photo editing application called PhotoDirector to take advantage of AMD's heterogeneous system architecture (HSA). It describes how photo editing pipelines involve computationally intensive RAW processing that could benefit from GPU acceleration. HSA allows sharing memory between the CPU and GPU to reduce bottlenecks. Performance tests show the potential for a 2x speedup using coarse-grained shared virtual memory buffers over OpenCL. The document concludes that HSA has great potential to improve performance for parallelizable and memory-intensive tasks in photo editing applications.
CC-4006, Deliver Hardware Accelerated Applications Using RemoteFX vGPU with W...AMD Developer Central
Presentation CC-4006, Deliver Hardware Accelerated Applications Using RemoteFX vGPU with Windows Server, by Derrick Isoka at the AMD Developer Summit (APU13) November 11-13, 2013
CC-4001, Aparapi and HSA: Easing the developer path to APU/GPU accelerated Ja...AMD Developer Central
Presentation CC-4001, Aparapi and HSA: Easing the developer path to APU/GPU accelerated Java applications, by Gary Frost and Vignesh Ravi at the AMD Developer Summit (APU13) Nov. 11-13, 2013.
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.
The document discusses the specifications and architecture of the AMD Radeon R9-290X graphics processing unit (GPU). Some key points:
- The R9-290X contains 44 compute units with a total of 2816 stream processors. It has a 512-bit GDDR5 memory interface providing 320 GB/sec of memory bandwidth.
- The GPU uses AMD's Graphics Core Next (GCN) architecture. This includes improvements to geometry processing, new local data share memory operations, and enhanced media processing instructions.
- The GCN architecture includes compute units containing vector units and a local data store. Compute units provide computational power through 2816 stream processors.
- New features include support for flat
Keynote (Phil Rogers) - The Programmers Guide to Reaching for the Cloud - by ...AMD Developer Central
Keynote presentation, The Programmers Guide to Reaching for the Cloud, by Phil Rogers, AMD Corporate Fellow, AMD, at the AMD Developer Summit (APU13), Nov. 11-13, 2013.
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
The document discusses HSA compiler technology. It outlines the architecture of HSA compilers, which leverage the LLVM framework and generate the HSAIL intermediate representation. Performance is improved through optimizations in the high-level compiler and a thin finalizer. OpenCL 2.0 features like shared virtual memory and platform atomics will be supported. The first release of the OpenCL/HSA compiler is planned for Q2 2014.
Mantle is a new low-level graphics API from EA that aims to simplify advanced game development and improve performance. It provides developers with more control over the GPU for optimizations. Mantle exposes the true capabilities of modern graphics hardware in a way that is accessible to developers. This allows for innovations like improved multi-GPU support, explicit resource management, and asynchronous compute. Mantle promises benefits like reduced driver overhead, better multi-threading, and more flexibility to optimize for all GPUs. EA sees Mantle driving future Frostbite engine designs by enabling new rendering techniques and optimizations.
Mantle allows Battlefield 4 to significantly improve CPU and GPU performance compared to DirectX 11. The game utilizes Mantle's low-level access to optimize shader compilation, pipeline state management, asynchronous compute and memory handling. Multi-GPU rendering is supported through Alternate Frame Rendering where resources are duplicated and updated asynchronously across GPUs.
Presentation & discussion around low-level graphics APIs. This was a quickly made presentation that I put together for a discussion with Intel and fellow ISVs, thought it could be worth sharing
Game engines have long been in the forefront of taking advantage of the ever
increasing parallel compute power of both CPUs and GPUs. This talk is about how the
parallel compute is utilized in practice on multiple platforms today in the Frostbite game
engine and how we think the parallel programming models, hardware and software in
the industry should look like in the next 5 years to help us make the best games possible.
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/
In this technical presentation Johan Andersson shows 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. He will go through the work of bringing over an advanced existing engine to an entirely new graphics API, the benefits and concrete details of doing low-level rendering on PC and how it fits into the architecture and rendering systems of Frostbite. Advanced optimization techniques and topics such as parallel dispatch, GPU memory management, multi-GPU rendering, async compute & async DMA will be covered as well as sharing experiences of working with Mantle in general.
Introduction to Software Defined Visualization (SDVis)Intel® Software
This document provides an overview of Intel's Software Defined Visualization (SDVis) initiative and updates on its current status. SDVis aims to enable scalable, flexible visualization that can run on a variety of systems from laptops to large clusters. It utilizes several open source libraries developed by Intel including Embree for ray tracing, OSPRay as a rendering engine, and OpenSWR for rasterization. The document discusses how SDVis addresses challenges of large-scale, high performance visualization. It provides examples of scientific visualization projects using SDVis and performance comparisons of Embree and OSPRay to GPU-based solutions. In addition, the document outlines several active integrations of SDVis technologies in visualization software including ParaView and
Stream processing is a computer programming paradigm that allows for parallel processing of data streams. It involves applying the same kernel function to each element in a stream. Stream processing is suitable for applications involving large datasets where each data element can be processed independently, such as audio, video, and signal processing. Modern GPUs use a stream processing approach to achieve high performance by running kernels on multiple data elements simultaneously.
RAPIDS – Open GPU-accelerated Data ScienceData Works MD
RAPIDS – Open GPU-accelerated Data Science
RAPIDS is an initiative driven by NVIDIA to accelerate the complete end-to-end data science ecosystem with GPUs. It consists of several open source projects that expose familiar interfaces making it easy to accelerate the entire data science pipeline- from the ETL and data wrangling to feature engineering, statistical modeling, machine learning, and graph analysis.
Corey J. Nolet
Corey has a passion for understanding the world through the analysis of data. He is a developer on the RAPIDS open source project focused on accelerating machine learning algorithms with GPUs.
Adam Thompson
Adam Thompson is a Senior Solutions Architect at NVIDIA. With a background in signal processing, he has spent his career participating in and leading programs focused on deep learning for RF classification, data compression, high-performance computing, and managing and designing applications targeting large collection frameworks. His research interests include deep learning, high-performance computing, systems engineering, cloud architecture/integration, and statistical signal processing. He holds a Masters degree in Electrical & Computer Engineering from Georgia Tech and a Bachelors from Clemson University.
This document summarizes Cass Everitt's presentation on the future of visual computing and OpenGL 4.4 on ARM architectures. Some key points include: ARM architectures are now dominant in mobile devices and embedded systems; OpenGL has become an important API for future development across many platforms; and OpenGL 4.4 introduces several new features that enable advanced rendering techniques on mobile devices. The presentation also discusses techniques like path rendering, ocean simulation, and PTEX virtual texturing that can improve graphics performance.
GPU Renderfarm with Integrated Asset Management & Production System (AMPS)Budianto Tandianus
This document describes a GPU renderfarm system integrated with an asset management and production system (AMPS) to efficiently manage rendering assets and accelerate the rendering process for CG movie production. The system allows artists around the world to upload and manage assets through AMPS. Rendering jobs are submitted online to a GPU renderfarm and monitored. Experiments showed nearly linear speedups from adding more GPU nodes, with render time decreasing from over 5 hours on one GPU to under 1.5 hours on two nodes with six GPUs total. Future work includes direct job submission from authoring tools and support for more tools, renderers, and heterogeneous renderfarm configurations.
1) The document discusses implementing and evaluating deep neural networks (DNNs) on mainstream heterogeneous systems like CPUs, GPUs, and APUs.
2) Preliminary results show that an APU achieves the highest performance per watt compared to CPUs and GPUs for DNN models like MLP and autoencoders.
3) Data transfers between the CPU and GPU are identified as a bottleneck, but APUs can help avoid this issue through efficient data sharing and zero-copy techniques between the CPU and GPU.
[Unite Seoul 2019] Mali GPU Architecture and Mobile Studio Owen Wu
The document discusses Mali GPU architecture and Arm Mobile Studio. It provides details on Mali GPU components like Bifrost shader cores and tile-based rendering. It also describes features such as index-driven vertex shading, forward pixel kill, and efficient render passes. The document concludes with an overview of the Arm Mobile Studio tools for profiling GPU and CPU performance on mobile devices.
IT Platform Selection by Economic Factors and Information Security Requiremen...ECLeasing
The document discusses selecting an IT platform for an SAP project based on economic factors and security requirements. It analyzes how different platforms like IBM Power, Sun Solaris, and IBM z/OS allocate resources for SAP hosts in high availability mode. The key considerations are the number of servers needed, acquisition costs, energy efficiency, and total cost of ownership over 5 years. Based on these factors, the best platform is chosen for the given SAP project's logical complexity and performance requirements.
Introduction to the Graphics Pipeline of the PS3Slide_N
This document provides an overview of the graphics pipeline in the PlayStation 3 (PS3) as presented by Cedric Perthuis. It describes the key hardware components like the Cell processor with its SPEs and RSX graphics processor. It also discusses the software APIs like PSGL, a version of OpenGL ES, and extensions developed for the PS3. Examples are provided of how to utilize the unique hardware architecture, such as using SPEs to preprocess particle system data.
Mirabilis_Design AMD Versal System-Level IP LibraryDeepak Shankar
Mirabilis Design provides the VisualSim Versal Library that enable System Architect and Algorithm Designers to quickly map the signal processing algorithms onto the Versal FPGA and define the Fabric based on the performance. The Versal IP support all the heterogeneous resource.
Spark is a powerful, scalable real-time data analytics engine that is fast becoming the de facto hub for data science and big data. However, in parallel, GPU clusters is fast becoming the default way to quickly develop and train deep learning models. As data science teams and data savvy companies mature, they will need to invest in both platforms if they intend to leverage both big data and artificial intelligence for competitive advantage.
This talk will discuss and show in action:
* Leveraging Spark and Tensorflow for hyperparameter tuning
* Leveraging Spark and Tensorflow for deploying trained models
* An examination of DeepLearning4J, CaffeOnSpark, IBM's SystemML, and Intel's BigDL
* Sidecar GPU cluster architecture and Spark-GPU data reading patterns
* Pros, cons, and performance characteristics of various approaches
Attendees will leave this session informed on:
* The available architectures for Spark and Deep Learning and Spark with and without GPUs for Deep Learning
* Several deep learning software frameworks, their pros and cons in the Spark context and for various use cases, and their performance characteristics
* A practical, applied methodology and technical examples for tackling big data deep learning
1. Building exascale computers requires moving to sub-nanometer scales and steering individual electrons to solve problems more efficiently.
2. Moving data is a major challenge, as moving data off-chip uses 200x more energy than computing with it on-chip.
3. Future computers should optimize for data movement at all levels, from system design to microarchitecture, to minimize energy usage.
The document discusses the evolution of GPU architecture and capabilities over time. It describes how GPUs have become massively parallel processors with programmable capabilities beyond just graphics. The document outlines the core components of a GPU including the graphics pipeline and programming model. It also discusses how GPUs are well suited for parallel, data-intensive applications and how their capabilities have expanded into general purpose computing through technologies like CUDA.
This document discusses new graphics APIs like DX12 and Vulkan that aim to provide lower overhead and more direct hardware access compared to earlier APIs. It covers topics like increased parallelism, explicit memory management using descriptor sets and pipelines, and best practices like batching draw calls and using multiple asynchronous queues. Overall, the new APIs allow more explicit control over GPU hardware for improved performance but require following optimization best practices around areas like parallelism, memory usage, and command batching.
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
This document discusses AMD's DirectGMA technology, which allows direct access to GPU memory from other devices. It introduces DirectGMA and explains how it enables peer-to-peer transfers between GPUs and GPUs and FPGAs. It then provides details on implementing DirectGMA in APIs like OpenGL, OpenCL, DirectX 9, 10 and 11 to enable efficient data transfers without CPU involvement.
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 document is about an AMD and Microsoft Game Developer Day event held in Stockholm, Sweden on June 2, 2014. It provides the date and location of the event multiple times but no other details.
This document discusses the TressFX hair and fur rendering technique. It begins by stating that next-gen quality hair is expected in current generation titles. It then covers the key components needed for high quality hair, including antialiasing, self-shadowing, and transparency. The document discusses isoline tessellation versus a vertex shader approach and describes TressFX's deferred rendering pipeline with selective shading of only the closest fragments. It demonstrates that TressFX can achieve next-gen quality hair and fur at real-time performance through techniques like variable ratio hair simulation, extrusion into triangles in the vertex shader, selective shading, and distance-based level of detail.
Low-level Shader Optimization for Next-Gen and DX11 by Emil PerssonAMD Developer Central
The document discusses low-level shader optimization techniques for next-generation consoles and DirectX 11 hardware. It provides lessons from last year on writing efficient shader code, and examines how modern GPU hardware has evolved over the past 7-8 years. Key points include separating scalar and vector work, using hardware-mapped functions like reciprocals and trigonometric functions, and being aware of instruction throughput and costs on modern GCN-based architectures.
The document summarizes a presentation given by Stephan Hodes on optimizing performance for AMD's Graphics Core Next (GCN) architecture. The presentation covers key aspects of the GCN architecture, including compute units, registers, and latency hiding. It then provides a top 10 list of performance advice for GCN, such as using DirectCompute threads in groups of 64, avoiding over-tessellation, keeping shader pipelines short, and batching drawing calls.
The document repeatedly states that AMD and Microsoft held a Game Developer Day event in Stockholm, Sweden on June 2, 2014 to work with game developers.
Direct3D12 aims to address issues with existing APIs by providing a more direct mapping to hardware capabilities. It features command buffers that allow work to be built in parallel threads and scheduled more efficiently. Pipeline state objects avoid runtime compilation overhead. Descriptor tables provide bindless resources through pointers and reduce state changes. While this gives more control and efficiency, it also means applications have more responsibility to avoid errors. Overall, Direct3D12 is designed to better expose the capabilities of modern graphics hardware.
Direct3D 12 aims to reduce CPU overhead and increase scalability across CPU cores by allowing developers greater control over the graphics pipeline. It optimizes pipeline state handling through pipeline state objects and reduces redundant resource binding by introducing descriptor heaps and tables. Command lists and bundles further improve performance by enabling parallel command list generation and reuse of draw commands.
Holy smoke! Faster Particle Rendering using Direct Compute by Gareth ThomasAMD Developer Central
The document discusses faster particle rendering using DirectCompute. It describes using the GPU for particle simulation by taking advantage of its parallel processing capabilities. It discusses using compute shaders to simulate particle behavior, handle collisions via the depth buffer, sort particles using bitonic sort, and render particles in tiles via DirectCompute to avoid overdraw from large particles. Tiled rendering involves culling particles, building per-tile particle indices, and sorting particles within each tile before shading them in parallel threads to composite onto the scene.
Productive OpenCL Programming An Introduction to OpenCL Libraries with Array...AMD Developer Central
This document provides an overview of OpenCL libraries for GPU programming. It discusses specialized GPU libraries like clFFT for fast Fourier transforms and Random123 for random number generation. It also covers general GPU libraries like Bolt, OpenCV, and ArrayFire. ArrayFire is highlighted as it provides a flexible array data structure and hundreds of parallel functions across domains like image processing, machine learning, and linear algebra. It supports JIT compilation and data-parallel constructs like GFOR to improve performance.
RapidFire - the Easy Route to low Latency Cloud Gaming Solutions - AMD at GDC14AMD Developer Central
RapidFire is a dedicated cloud gaming hardware and software solution from AMD that aims to simplify integration and deliver more high-definition game streams per GPU with low latency. It utilizes AMD hardware on both the server and client sides. The API provides functions for encoding and decoding video and audio streams, capturing input events, and displaying frames with low latency for cloud gaming applications. Eureva has implemented RapidFire in their Swiich solution to virtualize and stream any DirectX or OpenGL game in real-time with ultra-low latency over existing networks.
Mantle and Nitrous - Combining Efficient Engine Design with a modern API - AM...AMD Developer Central
Oxide Games Partners Dan Baker and Tim Kipp will show you how to build a high throughput renderer using the Mantle API in this AMD technology 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/
This AMD technology presentation from the 2014 Game Developers Conference in San Francisco March 17-21 explains how Mantle features can enable developers to improve both CPU and GPU performance in their titles. Also view this and other presentations at http://developer.amd.com/resources/documentation-articles/conference-presentations/
A look at how new Direct3D advancements enhance efficiency and enable fully-threaded building of command buffers in this prentation 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/
What is Model Context Protocol(MCP) - The new technology for communication bw...Vishnu Singh Chundawat
The MCP (Model Context Protocol) is a framework designed to manage context and interaction within complex systems. This SlideShare presentation will provide a detailed overview of the MCP Model, its applications, and how it plays a crucial role in improving communication and decision-making in distributed systems. We will explore the key concepts behind the protocol, including the importance of context, data management, and how this model enhances system adaptability and responsiveness. Ideal for software developers, system architects, and IT professionals, this presentation will offer valuable insights into how the MCP Model can streamline workflows, improve efficiency, and create more intuitive systems for a wide range of use cases.
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, presentation slides, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
#StandardsGoals for 2025: Standards & certification roundup - Tech Forum 2025BookNet Canada
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, transcript, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
Designing Low-Latency Systems with Rust and ScyllaDB: An Architectural Deep DiveScyllaDB
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Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-und-verwaltung-von-multiuser-umgebungen/
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Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
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Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
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👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
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5. Control
New model
Traditional Model:
Black Box
Explicit Model:
Mantle
Middle-ground abstraction – compromise
between performance & “usability”
Thin low-level abstraction to expose how
hardware works
Hidden resource memory & state
App explicit memory management
Resource CPU access tied to device context
Resources are globally accessible
Driver analyzes & synchronizes implicitly
App explicit resource state transitions
6. Control
App responsibility
Tell when render target will be used as a texture
‒ And many more resource state transitions
Don’t destroy resources that GPU is using
‒ Keep track with fences or frames
Manual dynamic resource renaming
‒ No DISCARD for driver resource renaming
Resource memory tiling
Powerful validation layer will help!
7. Control
Explicit control enables
App high-level decisions & optimizations
‒ Has full scene information
‒ Easier to optimize performance & memory
Flexible & efficient memory management
‒ Linear frame allocators
‒ Memory pools
‒ Pinned memory
Reduced development time
‒ For advanced game engines & apps
‒ Easier to get to target performance & robustness
8. Control
Explicit control enables
Transient resources
‒ Alias render targets within frame
‒ Major memory savings
‒ No need to pre-allocate everything
Light-weight driver
‒ Easier to develop & maintain
‒ Reduced CPU draw call overhead
11. CPU perf
Descriptor sets
Table with resource references to bind to
graphics or compute pipeline
Image
Memory
Sampler
Link
Replaces traditional resource stage binding
‒ Major performance & flexibility advantage
‒ Closer to how the hardware works
Example 1: Single simple dynamic descriptor set
‒ Bind everything you need for a single draw call
‒ Close to DX/GL model but share between stages
Dynamic descriptor set
VertexBuffer (VS)
Texture0 (VS+PS)
Constants (VS)
Texture1 (PS)
App managed - lots of strategies possible!
‒ Tiny vs huge sets
‒ Single vs multiple
‒ Static vs semi-static vs dynamic
Texture2 (PS)
Sampler0 (VS+PS)
12. CPU perf
Descriptor sets
Table with resource references to bind to
graphics or compute pipeline
Image
Link
‒ Reduce update time & memory usage
Memory
Sampler
Example 2: Reuse static set with nesting
Replaces traditional resource stage binding
‒ Major performance & flexibility advantage
‒ Closer to how the hardware works
App managed - lots of strategies possible!
‒ Tiny vs huge sets
‒ Single vs multiple
‒ Static vs semi-static vs dynamic
Static descriptor set
Dynamic descriptor set
Constants (VS)
Link
VertexBuffer (VS)
Texture0 (VS+PS)
Texture1 (PS)
Texture2 (PS)
Texture3 (PS)
Texture4 (PS)
Sampler0 (VS+PS)
Sampler1 (PS)
13. CPU perf
Monolithic pipelines
Shader stages & select graphics state combined into single object
‒ No runtime compilation or patching needed!
‒ Significantly less runtime overhead to use
Pipeline state
Supports parallel building & caching
‒ Fast loading times
Usage & management up to the app
‒ Static vs dynamic creation
‒ Amount of pipelines
‒ State usage
IA
VS
HS
DS
Tessellator
GS
RS
PS
DB
CB
14. CPU perf
Command buffers
Issue pipelined graphics & compute commands into a command buffer
‒ Bind graphics state, descriptor sets, pipeline
‒ Draw calls
‒ Render targets
‒ Clears
‒ Memory transfers
‒ NOT: resource mapping
Fully independent objects
‒ Create multiple every frame
‒ Or pre-build up front and reuse
15. CPU perf
CPU 0
CPU 1
CPU 2
DX/GL parallelism
Game
Game
Game
Render
Render
Driver Render
Automatically extracts parallelism out of most apps
Doesn’t scale beyond 2-3 cores
Additional latency
Driver thread often bottleneck – can collide app threads
Render
16. CPU perf
Parallel dispatch with Mantle
CPU 0
Game
Game
Game
CPU 1
Render
Render
Render
CPU 2
Render
Render
Render
CPU 3
Render
Render
Render
CPU 4
Render
Render
Render
App can go fully wide with its rendering – minimal latency
Close to linear scaling with CPU cores
No driver threads – no overhead – no contention
Frostbite’s approach on all consoles – and on PC with Mantle!
18. GPU perf
GPU optimizations
Thanks to improved CPU performance – CPU
will rarely be a bottleneck for the GPU
‒ CPU could help GPU more:
‒ Less brute force rendering
‒ Improve culling
Resource states
‒ Gives driver a lot more knowledge & flexibility
‒ Apps can avoid expensive/redundant transitions,
such as surface decompression
Expose existing GPU functionality
Shader pipeline object – driver optimizations
‒ Can optimize with pipeline state knowledge
‒ Can optimize across all shader stages
‒ Quad & Rect-lists
‒ HW-specific MSAA & depth data access
‒ Programmable sample patterns
‒ And more..
19. GPU perf
Queues
Modern GPUs are heterogeneous machines
with multiple engines
Graphics
‒ Graphics pipeline
‒ Compute pipeline(s)
‒ DMA transfer
‒ Video encode/decode
‒ More…
Mantle exposes queues for the engines +
synchronization primitives
Compute
DMA
...
Queues
GPU
21. GPU perf
Queue use cases
Async DMA transfers
‒ Copy resources in parallel with graphics or
compute
Copy
DMA
Graphics
Render
Other render
Use copy
22. GPU perf
Queue use cases
Async DMA transfers
‒ Copy resources in parallel with graphics or
compute
Async compute together with graphics
‒ ALU heavy compute work at the same time as
memory/ROP bound work to utilize idle units
Compute
Graphics
GBuffer
Non-shadowed lighting
Shadowmap 0
Shadowmap 1
Final lighting
23. GPU perf
Queue use cases
Async DMA transfers
Multiple compute kernels collaborating
‒ Copy resources in parallel with graphics or
compute
‒ Can be faster than über-kernel
‒ Example: Compute geometry backend & compute
rasterizer
Async compute together with graphics
‒ ALU heavy compute work at the same time as
memory/ROP bound work to utilize idle units
Compute 0
Compute 1
Graphics
Compute Geometry
Compute Rasterizer
Ordinary Rendering
24. GPU perf
Queue use cases
Async DMA transfers
Multiple compute kernels collaborating
‒ Copy resources in parallel with graphics or
compute
Async compute together with graphics
‒ ALU heavy compute work at the same time as
memory/ROP bound work to utilize idle units
Compute
Graphics
‒ Can be faster than über-kernel
‒ Example: Compute geometry backend & compute
rasterizer
Compute as frontend for graphics pipeline
‒ Compute runs asynchronously ahead and prepares
& optimizes geometry for graphics pipeline
Game Process1
large GPU
Process0 engines will buildProcess0 job graphs
‒ Move away from single sequential submission
Draw0
‒ Just as we already have doneDraw1
on CPU
Draw2
26. Programmability
Explicit Multi-GPU
Explicit control of GPU queues and synchronization, finally!
‒ Implement your own Alternate-Frame-Rendering
‒ Or something more exotic..
Use case: Workstation rendering with 4-8 GPUs
‒ Super high-quality rendering & simulation
‒ Load balance graphics & compute job graphs across GPUs
‒ 20-40 TFlops in a single machine!
Use case: Low-latency rendering
‒ Important for VR and competitive games
‒ Latency optimized GPU job graph scheduling
‒ VR: Simultaneously drive 2 GPUs (1 per eye)
27. Programmability
New mechanisms
Command buffer predication & flow control
‒ GPU affecting/skipping submitted commands
‒ Go beyond DrawIndirect / DispatchIndirect
‒ Advanced variable workloads
‒ Advanced culling optimizations
Write occlusion query results into GPU buffer
‒ No CPU roundtrip needed
‒ Can drive predicated rendering
‒ Or use results directly in shaders (lens flares)
28. Programmability
Bindless resources
Mantle supports bindless resources
‒ Shaders can select resources to use instead of
static binding from CPU
‒ Extension of the descriptor set support
Examples
‒ Performance optimizations – less data to update
‒ Logic & data structures that live fully on the GPU
‒ Scene culling & rendering
‒ Material representations
Key component that will open up a lot of
opportunities!
‒ Deferred shading
‒ Raytracing
30. Platforms
Today
Mantle gives us strong benefits on Windows today
‒ Console-like performance & programmability on both Windows 7 and Windows 8
‒ For us, well worth the dev time!
DX & GL are the industry standards
‒ Needed for platforms that do not support Mantle
‒ Needed by devs who do not want/need more control
‒ Have to have fallback paths for GL/DX, but not limit oneself to it
Mantle and PlayStation 4 will drive our future Frostbite designs & optimizations
‒ PS4 graphics API has great programmability & performance as well
‒ Share concepts, methods & optimization strategies
31. Platforms
Linux & Mac
Want to see Mantle on Linux and Mac!
‒ Would enable support for our full engine & rendering
‒ Significantly easier to do efficient renderer with Mantle than with OpenGL
Use cases:
‒ Workstations
‒ R&D
‒ Not limited by WDDM
‒ Games
‒ Mantle + SteamOS = powerful combination!
32. Platforms
Mobile
Mobile architectures are getting closer in capabilities to desktop GPUs
Want graphics API that allows apps to fully utilize the hardware
‒ Power efficient
‒ High performance
‒ Programmable
Major opportunity with Mantle – leap frog GL4, DX11
‒ For mobile SoC vendors
‒ For Google and Apple
33. Platforms
Multi-vendor?
Mantle is designed to be a thin hardware abstraction
‒ Not tied to AMD’s GCN architecture
‒ Forward compatible
‒ Extensions for architecture- and platform-specific functionality
Mantle would be a much more efficient graphics API for other vendors as well
‒ Most Mantle functionality can be supported on today’s modern GPUs
Want to see future version of Mantle supported on all platforms and on all modern GPUs!
‒ Become an active industry standard with IHVs and ISVs collaborating
‒ Enable us developers to innovate with great performance & programmability everywhere
35. Frostbite
Battlefield 4
Mantle support is in development
‒ Core renderer (closer to PS4 than DX11)
‒ Implement all rendering techniques used in BF4 (many!)
‒ CPU optimizations (parallel dispatch, descriptor sets)
‒ GPU optimizations (minimize transitions, MSAA)
‒ R&D for advanced GPU optimizations
‒ Memory management
‒ Multi-GPU support
‒ ~2 months of work
Update targeting late December
36. Frostbite
Plants vs Zombies: Garden Warfare
Very different rendering
compared to BF4
Frostbite Mantle renderer will
work out of the box
Focus on APU performance
37. Frostbite
Future
All Frostbite games designed with Mantle
‒ 15 games in development across all of EA
Advanced Mantle rendering & use cases
‒ Lots of exciting R&D opportunities!
Want multi-vendor & multi-platform support!