Gpu architecture pdf
Gpu architecture pdf. It adds many new features and delivers significantly faster performance for HPC, AI, and data analytics workloads. 8 terabytes per second (TB/s) —that’s nearly double the capacity of the NVIDIA H100 Tensor Core GPU with 1. Learn about the next massive leap in accelerated computing with the NVIDIA Hopper™ architecture. , output image size) Application provides GPU a buffer of vertices Application sends GPU a “draw” command: Jul 6, 2023 · However, the first chip to use the Ampere architecture was the GA100 – a data center GPU, 829mm 2 in size and with 54. nv-org-11 EE 7722 Lecture Transparency. GPU Computing Applications GPU Computing Software Libraries and Engines CUDA Compute Architecture Application Acceleration Engines (AXEs) SceniX, CompleX,Optix, PhysX Foundation Libraries CUBLAS, CUFFT, CULA, NVCUVID/VENC, NVPP, Magma Development Environment C, C++, Fortran, Python, Java, OpenCL, Direct Compute, … A high-level overview of NVIDIA H100, new H100-based DGX, DGX SuperPOD, and HGX systems, and a H100-based Converged Accelerator. The evolution of GPU hardware architecture has gone from a specific single core, fixed function hardware pipeline implementation made solely for graphics, to a set of highly parallel and programmable cores for more general purpose computation. NVIDIA’s next‐generation CUDA architecture (code named Fermi), is the latest and greatest expression of this trend. The first implementation of the “Vega” architecture is the “Vega” 10 GPU. SGEMM performance on the GPU architecture; it 2. The newest members of the NVIDIA Ampere architecture GPU family, GA102 and GA104, are described in this whitepaper. The H200’s larger and faster memory accelerates generative AI and LLMs, while Mar 30, 2020 · View PDF Abstract: Many deep learning models, developed in recent years, reach higher ImageNet accuracy than ResNet50, with fewer or comparable FLOPS count. On November 3, AMD revealed key details of its RDNA 3 GPU architecture and the Radeon RX 7900-series graphics cards. It was fabricated by TSMC, using their N7 node (the A high-level overview of NVIDIA H100, new H100-based DGX, DGX SuperPOD, and HGX systems, and a H100-based Converged Accelerator. With The World’s Most Advanced Data Center GPU WP-08608-001_v1. GPU is a partner chip, has a distinct set of memory Sections of code will feel like Distributed architecture CPU / GPU memory transfers Barriers / synchronization as CPU waits for GPU to finish GPU itself is like a multicore system on steroids 4 NVIDIA Tesla architecture (2007) First alternative, non-graphics-speci!c (“compute mode”) interface to GPU hardware Let’s say a user wants to run a non-graphics program on the GPU’s programmable cores… -Application can allocate bu#ers in GPU memory and copy data to/from bu#ers -Application (via graphics driver) provides GPU a single Jan 26, 2017 · PDF | In this paper, we present a methodology to understand GPU microarchitectural features and improve performance for compute-intensive kernels. Figure 2 – Adjacent Compute Unit Cooperation in RDNA architecture. Turing was the world’s first GPU architecture to offer high The AMD Instinct™ MI100 accelerator is the world’s fastest HPC GPU, and a culmination of the AMD CDNA architecture, with all-new Matrix Core Technology, and AMD ROCm™ open ecosystem to deliver new levels of performance, portability, and productivity. 3D modeling software or VDI infrastructures. We would like to show you a description here but the site won’t allow us. Summary Based on the NVIDIA Hopper™ architecture, the NVIDIA H200 is the first GPU to offer 141 gigabytes (GB) of HBM3e memory at 4. This allows the P100 to tackle much larger working sets of data at higher bandwidth, improving efficiency and computational throughput, and reduce the NVIDIA H100 GPU Architecture In- Depth 17 H100 SM Architecture 19 H100 SM Key Feature Summary 22 H100 Tensor Core Architecture 22 Hopper FP8 Data Format 23 New DPX Instructions for Accelerated Dynamic Programming 27 Combined L1 Data Cache and Shared Memory 27 H100 Compute Performance Summary 28 H100 GPU Hierarchy and Asynchrony Improvements 29 DLSS 3 is a full-stack innovation that delivers a giant leap forward in real-time graphics performance. 6: GPU’s Stream Processor. The Metal Shading Language is typically used to program these GPUs, and this document uses Metal terminology. NVIDIA engineers set clear design goals for every new GPU architecture. Instructions. Turing represents the biggest architectural leap forward in over a decade, providing a new core GPU architecture that enables major advances in efficiency and performance for PC gaming, professional graphics applications, and deep learning inferencing. Download full-text PDF. The new dual compute unit design is the essence of the RDNA architecture and replaces the GCN compute unit as the fundamental computational building block of the GPU. Powered by t he NVIDIA Ampere architecture- based GA100 GPU, the A100 provides very strong scaling for GPU compute and deep learning time; the GPU assembles vertices into triangles as needed. Each NVIDIA GPU Architecture is carefully designed to provide breakthrough Sep 14, 2018 · The new NVIDIA Turing GPU architecture builds on this long-standing GPU leadership. 7 and newer) architecture paradigm. The Intel® Processor Graphics Gen11 Architecture 9 4. For example, \NVIDIA Tesla V100 GPU Architecture" v1. •Several reasons: •Competitive advantage •Fear of being sued by “non-practicing entities” •The people that know the details too busy building the next chip •Model described next, embodied in GPGPU-Sim, developed from: May 4, 2011 · • Graphics Processing Unit (GPU) • A specialized circuit designed to rapidly manipulate and alter memory • Accelerate the building of images in a frame buffer intended for output to a display • GPU -> General Purpose Graphics Processing Unit (GPGPU) • A general purpose graphics processing unit as a modified form of stream processor GPU Architecture •GPUs consist of Streaming Multiprocessors (SMs) •NVIDIA calls these streaming multiprocessors and AMD calls them compute units •SMs contain Streaming Processors (SPs) or Processing Elements (PEs) •Each core contains one or more ALUs and FPUs •GPU can be thought of as a multi-multicore system Global Memory Shared HBM2 High-Speed GPU Memory Architecture Tesla P100 is the world’s first GPU architecture to support HBM2 memory. Shows functional units in a oorplan-like diagram of an SM. Jan 1, 2012 · Download full-text PDF Read full-text. As Figure 2 illustrates, the dual compute unit still comprises four SIMDs that operate independently. Copy link Link copied. While FLOPs are often seen as a proxy for network efficiency, when measuring actual GPU training and inference throughput, vanilla ResNet50 is usually significantly faster than its recent competitors, offering better throughput-accuracy Nov 10, 2022 · In this post, you learn all about the Grace Hopper Superchip and highlight the performance breakthroughs that NVIDIA Grace Hopper delivers. NVIDIA Ampere GA102 GPU Architecture 5 Introduction Since inventing the world’s first GPU (Graphics Processing Unit) in 1999, NVIDIA GPUs have been at the forefront of 3D graphics and GPU-accelerated computing. Mar 22, 2022 · H100 SM architecture. Using new NVIDIA H100 GPU Architecture In- Depth 17 H100 SM Architecture 19 H100 SM Key Feature Summary 22 H100 Tensor Core Architecture 22 Hopper FP8 Data Format 23 New DPX Instructions for AcceleratedDynamic Programming 27 Combined L1 Data Cache and Shared Memory 27 H100 Compute Performance Summary 28 H100 GPU Hierarchy and Asynchrony Improvements 29 NVIDIA Pascal architecture is purpose-built GPU to be the engine of computers that learn, see & simulate data center Pascal Tesla P100 is built to meet the demands of next generations displays, including VR and ultra-high-resolution monitors. GPU CPU – Really fast caches (great for data reuse) – Fine branching granularity – Lots of different processes/threads – High performance on a single thread of execution GPU – Lots of math units – Fast access to onboard memory – Run a program on each fragment/vertex – High throughput on parallel tasks The NVIDIA Grace CPU leverages the flexibility of the Arm® architecture to create a CPU and server architecture designed from the ground up for accelerated computing. This is followed by a deep dive into the H100 hardware architecture, efficiency improvements, and new programming features. With many times the performance of any conventional CPU on parallel software, and new features to make it but there are clear trends towards tight-knit CPU-GPU integration. Mapping Programming Models to Architecture(Jason) 8. The main contributions of this paper are as follows: We demystify the Nvidia Ampere [11] GPU architecture through microbenchmarking by measuring the clock cy-cles latency per instruction on different data types. Gen Compute Architecture (Maiyuran) Execution units 5. GA102 and GA104 are part of the new NVIDIA “GA10x” class of Ampere architecture GPUs. Each major new architecture release is accompanied by a new version of the CUDA Toolkit, which includes tips for using existing code on newer architecture GPUs, as well as instructions for using new features only available when using the newer GPU architecture. Applications that run on the CUDA architecture can take advantage of an GPU simulators. The H200’s larger and faster memory accelerates generative AI and LLMs, while The NVIDIA® Grace Hopper architecture brings together the groundbreaking performance of the NVIDIA Hopper GPU with the versatility of the NVIDIA Grace™ CPU, connected with a high bandwidth and memory coherent NVIDIA NVLink Chip-2-Chip (C2C)® interconnect in a single Superchip, and support for the new NVIDIA NVLink Switch System. –Develop intuition for what they can do well. The sec-ond line loads this large array into GPU’s memory. Graphics Technology Interface (GTI) is the gateway between GPU and the rest of the SoC. Compute Architecture Evolution (Jason) 3. gpu_y = sin(gpu_x); cpu_y = gather(gpu_y); The first line creates a large array data structure with hundreds of millions of decimal numbers. ) Computer Architecture and Oct 29, 2020 · A Graphics Processor Unit (GPU) is mostly known for the hardware device used when running applications that weigh heavy on graphics, i. With the addition of CUDA and GPU computing to the capabilities of the GPU, it is now possible to use the GPU as both a graphics processor and a computing processor at the same time, and to combine these uses in visual computing applications. The following Architecture Terminology Changes table maps legacy GPU terminologies (used in Generation 9 through Generation 12 Intel ® Core TM architectures) to their new names in the Intel ® Iris ® X e GPU (Generation 12. Sep 14, 2018 · But if you can’t wait and want to learn about all the technology in advance, you can download the 87-page NVIDIA Turing Architecture Whitepaper. –Understand key patterns for building your own pipelines. Chapter 2 provides a summary of GPU programming models relevant to the rest of the book. Over the past four years, there have been approximately 20 papers per year focusing on GPU-design at the top architecture conferences. Applications that run on the CUDA architecture can take advantage of an GPU Task Parallelism • Multiple processing units (SMs/cores), each with its own kernel and local memory • Multiple chips on a single GPU • Multiple GPUs (SLI/Crossfire) in a machine • (CPU + GPU) • Multiple machines on a network cluster May 16, 2023 · This chapter explores the historical background of current GPU architecture, basics of various programming interfaces, core architecture components such as shader pipeline, schedulers and memories that support SIMT execution, various types of GPU device memories and their performance characteristics, and some examples of optimal data mapping to Jun 5, 2023 · AMD RDNA 3 Introduction. See examples of GPU history, rendering, shaders, and data-parallelism. GA10x GPUs build on the revolutionary NVIDIA Turing™ GPU architecture. This document provides an overview of the AMD RDNA 3 scheduling architecture by describing the key scheduler firmware (MES) and hardware (Queue Manager) components that participate in the scheduling. This breakthrough software leverages the latest hardware innovations within the Ada Lovelace architecture, including fourth-generation Tensor Cores and a new Optical Flow Accelerator (OFA) to boost rendering performance, deliver higher frames per second (FPS), and significantly improve latency. It was a public announcement that the whole world was Introduction to the NVIDIA Ampere GA102 GPU Architecture . Hopper securely scales diverse workloads in every data center, from small enterprise to exascale high-performance computing (HPC) and trillion-parameter AI—so brilliant innovators can fulfill their life's work at the fastest pace in human history. Chapter 4 explores the A trend towards GPU programmability was starting to form. The CUDA architecture is a revolutionary parallel computing architecture that delivers the performance of NVIDIA’s world-renowned graphics processor technology to general purpose GPU Computing. Due to the limited space, CMU School of Computer Science Aug 15, 2023 · 7. Chapter 4 explores the architecture of the GPU memory system. The third executes the sin function on each individual number of the array inside the GPU. org. Three major ideas that make GPU processing cores run fast 2. Equipped with eight NVIDIA Blackwell GPUs interconnected with fifth-generation NVIDIA® NVLink®, DGX B200 delivers leading-edge performance, offering 3X the training performance and 15X the inference performance of previous generations. We first seek to understand state of the art GPU architectures and examine GPU design proposals to reduce performance loss caused by SIMT thread divergence. g. Turing provided major advances in efficiency and performance for PC gaming, professional graphics applications, and deep learning inferencing. In the consumer market, a GPU is mostly used to accelerate gaming graphics. 1. Our discovery work needs to be repeated anew on each future architecture; developers that use the CUDA libraries and the NVCC compiler with-out our optimizations already benet from an excellent combination of GPU Whitepaper. The relative popularity of GPGPU-Sim can be attributed to several factors, but it’s most appealing Feb 21, 2024 · This study makes the first attempt to demystify the tensor core performance and programming instruction sets unique to Hopper GPUs, which are expected to greatly facilitate software optimization and modeling efforts for GPU architectures. The extensive use of GPU was in the field of gaming and rendering of 30 graphics. This is based on reverse engineering and is likely to have mistakes. Instruction Set Architecture (Ken) 6. This con-venience comes at a price: before rendering, the GPU must first trans- CUDA Abstractions A hierarchy of thread groups Shared memories Barrier synchronization CUDA Kernels Executed N times in parallel by N different CUDA Compute and Graphics Architecture, Code-Named “Fermi” The Fermi architecture is the most significant leap forward in GPU architecture since the original G80. For example, in Figure 5, Page 13. Apr 18, 2018 · View PDF Abstract: Every year, novel NVIDIA GPU designs are introduced. • Mar 25, 2021 · Understanding the GPU architecture To fully understand the GPU architecture, let us take the chance to look again the first image in which the graphic card appears as a “sea” of computing cores. “Vega” 10 is a relatively large-scale chip meant to serve multiple markets, including high-resolution gaming and VR, the most intensive workstation-class applications, and the GPU computing space, including key vertical markets like HPC and machine learning. With its groundbreaking RT and Tensor Cores, the Turing architecture laid the foundation for a new era in graphics, which includes ray tracing and AI-based neural graphics. This white paper covers the Turing SM, memory, display, and NVLink enhancements, as well as the NGX and DLSS software platforms. 4 Generation VI The introduction of NVIDIA's GeForce 8 series GPU in 2006 marked the next step in GPU evolution: exposing the GPU as massively parallel processors [4]. Modern GPU Microarchitectures. , programmable GPU pipelines, not their fixed-function predecessors. Th e underlying processor architecture of the GPU is exposed in two academic research on GPU architectures. AMD InstinctTM MI250X, at the heart of the first Exascale system, was enabled by the AMD CDNA™ 2 architecture and advanced packaging, as well as AMD Infinity Fabric™, connecting the Explore an extensive archive of e-prints in the fields of physics, mathematics, computer science, and more on arXiv. Pre-Pascal GPUS –managed by software, limited to GPU memory size • CPU-to-GPU • GPU grid-to-grid … One-shot CPU-to-GPU graph submission and graph reuse Microarchitecture improvements for grid-to-grid latencies →S21760: CUDA New Features And Beyond, 5/19 10:15am PDT 32-node graphs of empty grids, DGX1-V, DGX-A100 Title: Microsoft PowerPoint - ORNL Application Readiness Workshop - AMD GPU Basics Author: nmalaya Created Date: 10/14/2019 9:23:27 PM NVIDIA DGX™ B200 is an unified AI platform for develop-to-deploy pipelines for businesses of any size at any stage in their AI journey. For more information about the speedups that Grace Hopper achieves over the most powerful PCIe-based accelerated platforms using NVIDIA Hopper H100 GPUs, see the NVIDIA Grace Hopper Superchip Architecture whitepaper. 2 billion transistors. . It details Turing’s GPU design, game-changing Ray Tracing technology, performance-accelerating D ee p Learning Super Sampling (DLSS), innovative shading advancements, and much more. Using new hardware-based ac 1. This document is intended to introduce the reader to the overall scheduling architecture and is not meant to serve as a programming guide. Heterogeneous Cores CPU vs. The PDF document covers topics such as ray tracing, tensor cores, GDDR6X, RTX IO, and more. Li, and the H&P book, 5th Ed. The fast, affordable GPU computing products. Tesla V100 GPU, adding many new features while delivering significantly faster performance for HPC, AI, and data analytics workloads. In this work, we will examine existing research directions and future opportunities for chip integrated CPU-GPU systems. Read full-text. Mar 12, 2015 · ARM Mali GPU Architecture Sam Martin ARM Game Developer Day - London Graphics Architect, ARM 03/12/2015 Blackwell-architecture GPUs pack 208 billion transistors and are manufactured using a custom-built TSMC 4NP process. We show the mapping of PTX instructions to the sass AMD has pioneered the evolution of system architecture over the last decade to unify CPU and GPU computing at an unparalleled scale. Learn about the features and performance of the second-generation RTX GPUs based on the Ampere architecture. A PDF file about general-purpose graphics processor architecture, uploaded by tpn on GitHub. Learn about the evolution of GPUs from fixed function to unified scalar shader architecture, and the features and benefits of CUDA-based GPU computing. This can be used to partition the GPU into as many as seven hardware-isolated GPU instances, providing a unified platform that enables elastic data centers to adjust dynamically to shifting workload demands. 63 Mar 23, 2023 · Graphic Programming Unit (GPU) is a parallel processor designed with high computational ability. Graphics Processing Units (GPUs) Stéphane Zuckerman (Slides include material from D. The graphics processing unit (GPU) is a specialized and highly parallel microprocessor designed to offload and accelerate 2D or 3D rendering from the Section “Recent Research on GPU Architecture” discusses research trends to improve performance, energy efficiency, and reliability of GPU architecture. Chapter 3 explores the architecture of GPU compute cores. May 14, 2020 · The NVIDIA A100 Tensor Core GPU is based on the new NVIDIA Ampere GPU architecture, and builds upon the capabilities of the prior NVIDIA Tesla V100 GPU. e. Orozco, J. 4. Building upon the NVIDIA A100 Tensor Core GPU SM architecture, the H100 SM quadruples the A100 peak per SM floating point computational power due to the introduction of FP8, and doubles the A100 raw SM computational power on all previous Tensor Core, FP32, and FP64 data types, clock-for-clock. Learn more from this deep dive into the NVIDIA Grace Hopper GPUs. 4X more memory bandwidth. The GPU memory hierarchy: moving data to processors 4. i. NVIDIA Ada GPU Architecture . 3. Model transformations A GPU can specify each logical object in a scene in its own locally defined coordinate system, which is convenient for objects that are natu-rally defined hierarchically. Introduction . Sep 16, 2020 · Our new GeForce RTX 30 Series graphics cards are powered by NVIDIA Ampere architecture GA10x GPUs, which bring record breaking performance to PC gamers worldwide. Launched in 2018, NVIDIA’s® Turing™ GPU Architecture ushered in the future of 3D graphics and GPU-accelerated computing. Download slides as PDF [Course Info] [Lectures/Readings] Lecture 7: GPU architecture and CUDA Programming. Due to the limited space, CMU School of Computer Science GPUs. %PDF-1. 1 GLOBAL ASSETS, MEDIA FF AND GTI Global Assets presents a hardware and software interface from GPU to the rest of the SoC including Power Management. For example a CPU SIMD-lane is a Metal thread, and a CPU thread is a Metal Based on the NVIDIA Hopper™ architecture, the NVIDIA H200 is the first GPU to offer 141 gigabytes (GB) of HBM3e memory at 4. Download slides as PDF AMD CDNATM 2 Architecture Overview The AMD CDNA™ 2 architecture builds on the tremendous core strengths of the original AMD CDNA architecture to deliver a leap forward in system performance and usability while using a similar process technology. All the enhancements and features supported by our new GPUs are detailed in full on our website, but if you want an 11,000 word deep dive into all the architectural nitty gritty of our latest graphics cards, you should download the first step in accurately modeling the Ampere GPU architecture. Graphics processing units (GPUs) are continually evolving to cater to the computational demands of contemporary general-purpose workloads, particularly those AMD Data Center GPU Lineup Top-to-bottom open ecosystem commitment AMD CDNA™ architecture AMD CDNA 2 architecture Strategic development with lead customers ROCm™Software AMD Instinct™MI100 Accelerator AMD Instinct™MI200 Accelerator Customer-Oriented Data Center Solutions World-class GPU Accelerator Technologies Open Software Ecosystem . Their perfor-mance gains will not port to future GPU architectures. Closer look at real GPU designs –NVIDIA GTX 580 –AMD Radeon 6970 3. The file is part of a repository that contains various PDFs on computer science topics. GT200 extended the performance and functionality of G80. Illustration 6: Unified hardware shader design The G80 (GeForce 8800) architecture was the first to have The NVIDIA H100 PCIe card features Multi-Instance GPU (MIG) capability. GPU architecture, the m emory is divided in 16 banks. Chip Level Architecture (Jason) Subslices, slices, products 4. Memory Sharing Architecture (Jason) 7. Apr 18, 2018 · our optimizations are specic to the Volta architecture. Today, GPGPU’s (General Purpose GPU) are the choice of hardware to accelerate computational workloads in modern High Performance Section “Recent Research on GPU Architecture” discusses research trends to improve performance, energy efficiency, and reliability of GPU architecture. nv-org-11 GPU Microarchitecture •Companies tight lipped about details of GPU microarchitecture. All Blackwell products feature two reticle-limited dies connected by a 10 terabytes per second (TB/s) chip-to-chip interconnect in a unified single GPU. The first chapter of this book describes the basic hardware structure of GPUs and provides a brief overview of their history. After describing the architecture of existing systems, Chapters 3 and 4 provide an overview of related research. Due to the important role of GPUs to many computing fields, GPU architecture is one of the most actively researched domains in last decade. CUDA Compute capability allows developers to determine the features supported by a GPU. Learn about the features and technologies of the NVIDIA Turing GPU architecture, such as ray tracing, tensor cores, mesh shading, and more. Summary 2. G80 was our initial vision of what a unified graphics and computing parallel processor should look like. This PDF presentation covers the history, details and examples of modern GPU architecture and programming. Let’s say a user wants to draw a picture using a GPU…-- -- Application (via graphics driver) provides GPU vertex and fragment shader program binaries Application sets graphics pipeline parameters (e. . 80% of those papers have used today’s most popular open-source GPU simulator, GPGPU-Sim [2]. This rapid architectural and technological progression, coupled with a reluctance by manufacturers to disclose low-level details, makes it difficult for even the most proficient GPU software designers to remain up-to-date with the technological advances at a microarchitectural level. The Hopper GPU is paired with the Grace CPU using NVIDIA’s ultra-fast chip-to-chip interconnect, delivering 900GB/s of bandwidth, 7X faster than PCIe Gen5. The AMD CDNA architecture is an excellent starting point for a computational platform. 1 | 1 INTRODUCTION TO THE NVIDIA TESLA V100 GPU ARCHITECTURE Since the introduction of the pioneering CUDA GPU Computing platform over 10 years ago, each new NVIDIA® GPU generation has delivered higher application performance, improved power Feb 21, 2024 · View a PDF of the paper titled Benchmarking and Dissecting the Nvidia Hopper GPU Architecture, by Weile Luo and 5 other authors View PDF HTML (experimental) Abstract: Graphics processing units (GPUs) are continually evolving to cater to the computational demands of contemporary general-purpose workloads, particularly those driven by artificial Intel® Processor Graphics Gen11 Architecture 9 4. Using new Nvidia How to think about scheduling GPU-style pipelines Four constraints which drive scheduling decisions • Examples of these concepts in real GPU designs • Goals –Know why GPUs, APIs impose the constraints they do. HBM2 offers three times (3x) the memory bandwidth of the Maxwell GM200 GPU. Siegel, Professor X. • GPU architectures −AMD Sourthern Islands GPU Architecture −Nvidia Fermi GPU Architecture −Cell Broadband Engine • OpenCL Specific Topics −OpenCL Compilation System −Installable Client Driver (ICD) TOPICS GPU Architecture Unified L2 cache (100s of Kb) Fast, coherent data sharing across all cores in the GPU Unified/Managed Memory Since CUDA6 it’s possible to allocate 1 pointer (virtual address) whose physical location will be managed by the runtime. Learn how GPUs evolved from graphics processors to parallel compute engines for various applications, and how to program them using CUDA language. 5 % 20 0 obj /Filter /FlateDecode /Length 4583 >> stream xÚ [YsÜF’~ׯàÛ4#H … ~£%ÓöŒdk-zv'h>€èb7B8Ú8Ls~ýä—Y…‹hiwCÁFVfÝ•w•Ü‹Ã Figure 20. Download citation. This document attempts to describe the Apple G13 GPU architecture, as used in the M1 SoC. 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