ArticleController :: show
Request
GET Parameters
None
POST Parameters
None
Uploaded Files
None
Request Attributes
Key | Value |
---|---|
_controller | "App\Controller\ArticleController::show" |
_firewall_context | "security.firewall.map.context.main" |
_links | Symfony\Component\WebLink\GenericLinkProvider {#3600 -links: [ 3721 => Symfony\Component\WebLink\Link {#3721 -href: "/build/runtime.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3719 => Symfony\Component\WebLink\Link {#3719 -href: "/build/644.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3718 => Symfony\Component\WebLink\Link {#3718 -href: "/build/502.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3717 => Symfony\Component\WebLink\Link {#3717 -href: "/build/app.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3716 => Symfony\Component\WebLink\Link {#3716 -href: "/build/view-more.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3715 => Symfony\Component\WebLink\Link {#3715 -href: "/build/term-condition.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3714 => Symfony\Component\WebLink\Link {#3714 -href: "/build/contact.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3713 => Symfony\Component\WebLink\Link {#3713 -href: "/build/scroll-infinite-article.js" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "script" ] } 3712 => Symfony\Component\WebLink\Link {#3712 -href: "/build/app.css" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "style" ] } 3711 => Symfony\Component\WebLink\Link {#3711 -href: "/build/cookie-style.css" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "style" ] } 3710 => Symfony\Component\WebLink\Link {#3710 -href: "/build/term-condition-css.css" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "style" ] } 3709 => Symfony\Component\WebLink\Link {#3709 -href: "/build/contact-css.css" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "style" ] } 3708 => Symfony\Component\WebLink\Link {#3708 -href: "/build/comment-css.css" -rel: [ "preload" => "preload" ] -attributes: [ "as" => "style" ] } ] } |
_route | "article_show" |
_route_params | [ "category" => "technology" "slug" => "are-the-highly-marketed-deep-learning-and-machine-learning-processors-just-simple-matrix-multiplication-accelerators" ] |
_security_firewall_run | "_security_main" |
_stopwatch_token | "71e72d" |
category | "technology" |
slug | "are-the-highly-marketed-deep-learning-and-machine-learning-processors-just-simple-matrix-multiplication-accelerators" |
Request Headers
Header | Value |
---|---|
accept | "*/*" |
accept-encoding | "gzip, br, zstd, deflate" |
connection | "close" |
cookie | "PHPSESSID=s31pot4h2o95h5alvk1ltm7s0m" |
host | "rct.dev.bbntimes.com" |
user-agent | "Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)" |
x-php-ob-level | "1" |
Request Content
Request content not available (it was retrieved as a resource).
Response
Response Headers
Header | Value |
---|---|
cache-control | "no-cache, private" |
content-type | "text/html; charset=UTF-8" |
date | "Sat, 22 Feb 2025 13:14:20 GMT" |
link | "</build/runtime.js>; rel="preload"; as="script",</build/644.js>; rel="preload"; as="script",</build/502.js>; rel="preload"; as="script",</build/app.js>; rel="preload"; as="script",</build/view-more.js>; rel="preload"; as="script",</build/term-condition.js>; rel="preload"; as="script",</build/contact.js>; rel="preload"; as="script",</build/scroll-infinite-article.js>; rel="preload"; as="script",</build/app.css>; rel="preload"; as="style",</build/cookie-style.css>; rel="preload"; as="style",</build/term-condition-css.css>; rel="preload"; as="style",</build/contact-css.css>; rel="preload"; as="style",</build/comment-css.css>; rel="preload"; as="style"" |
x-debug-token | "3e627d" |
Cookies
Request Cookies
Key | Value |
---|---|
PHPSESSID | "s31pot4h2o95h5alvk1ltm7s0m" |
Response Cookies
No response cookies
Session 6
Session Metadata
Key | Value |
---|---|
Created | "Sat, 22 Feb 25 13:13:57 +0000" |
Last used | "Sat, 22 Feb 25 13:14:19 +0000" |
Lifetime | 0 |
Session Attributes
Attribute | Value |
---|---|
_csrf/https-comment | "0ipYS-bAY6RjuR5WMp8c6-3q9VGgXPsB95tlHIqN1dI" |
_csrf/https-cookie_accept | "nnYasNILGl-fodfrQVkl5UQK6F9GRC17yup2_jbgUzo" |
Session Usage
6
Usages
Stateless check enabled
Usage |
---|
Symfony\Component\Security\Csrf\TokenStorage\SessionTokenStorage:76
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Symfony\Component\Security\Csrf\TokenStorage\SessionTokenStorage:79
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Symfony\Component\Security\Csrf\TokenStorage\SessionTokenStorage:52
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Symfony\Component\Security\Csrf\TokenStorage\SessionTokenStorage:56
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Symfony\Component\Security\Core\Authentication\Token\Storage\UsageTrackingTokenStorage:41
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current_article | App\Entity\Article {#1094 -id: 9439 -title: "Are The Highly-Marketed Deep Learning and Machine Learning Processors Just Simple Matrix-Multiplication Accelerators?" -slug: "are-the-highly-marketed-deep-learning-and-machine-learning-processors-just-simple-matrix-multiplication-accelerators" -introtext: "<p><a href="companies/understanding-artificial-intelligence-machine-learning-and-deep-learning" target="_blank">Artificial intelligence (AI) </a>accelerators are computer systems<span style="font-size: 10.8333px;"> </span>designed to enhance artificial intelligence and machine learning applications, including artificial neural networks (ANNs) and machine vision. </p>\r\n" -content: """ \r\n <p>Most AI accelerators are just simple data matrix-multiplication accelerators. All the rest is commercial propaganda.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">The main aim of this article is to understand the complexity of machine learning (ML) and deep learning (DL) processors and discover the truth about the so-called <a href="https://www.synopsys.com/ai/what-is-an-ai-accelerator.html" target="_blank" rel="noopener">AI accelerators</a>. </p>\r\n <p class="gmail-q-text gmail-qu-display--block">Unlike other computational devices that treat scalar or vectors as primitives, Google’s Tensor Process Unit (TPU) ASIC treats matrices as primitives,The TPU is designed to perform matrix multiplication at a massive scale.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">At its core, you find something that is inspired by the heart and not the brain. It’s called a “Systolic Array” described in 1982 in “<span class="gmail-q-inline"><a class="gmail-q-box gmail-qu-cursor--pointer gmail-qu-hover--textDecoration--underline gmail-Link___StyledBox-t2xg9c-0 gmail-roKEj" title="www.eecs.harvard.edu" href="http://www.eecs.harvard.edu/~htk/publication/1982-kung-why-systolic-architecture.pdf" target="_blank" rel="nofollow noopener">Why Systolic Architectures</a>"</span>?<span class="gmail-q-inline"></span></p>\r\n <p class="gmail-q-text gmail-qu-display--block">And this computational device contains 256 x 256 8bit multiply-add computational units. A grand total of 65,536 processors is capable of 92 trillion operations per second.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">It uses DDR3 with only 30GB/s to memory. Contrast that to the Nvidia Titan X with GDDR5X hitting transfer speeds of 480GB/s.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">Whatever, it has nothing to do with real AI hardware.</p>\r\n <h2 class="gmail-q-text gmail-qu-display--block">Some General Reflections on Processing Units and Narrow AI Coprocessors</h2>\r\n <p class="gmail-q-text gmail-qu-display--block">A central main processor is commonly defined as a digital circuit which performs operations on some external data source, usually memory or some other data stream, taking the form of a microprocessor implemented on a single metal–oxide–semiconductor integrated circuit chip (MOSFET).</p>\r\n <p class="gmail-q-text gmail-qu-display--block">It could be supplemented with a coprocessor, performing floating point arithmetic, graphics, signal processing, string processing, cryptography, or I/O interfacing with peripheral devices. Some application-specific hardware units include video cards for graphics, sound cards, graphics processing units and digital signal processors.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">A central processing unit (CPU), also called a central processor, main processor or just processor, is the electronic circuitry that executes instructions comprising a computer program. The CPU performs basic arithmetic, logic, controlling, and input/output (I/O) operations specified by the instructions in the program.</p>\r\n <ul>\r\n <li class="gmail-q-text gmail-qu-display--block">Microprocessor chips with multiple CPUs are multi-core processors.</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Array processors or vector processors have multiple processors that operate in parallel, with no unit considered central. Virtual CPUs are an abstraction of dynamical aggregated computational resources.</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Microprocessor chips with multiple CPUs are multi-core processors.</li>\r\n </ul>\r\n <p class="gmail-q-text gmail-qu-display--block">There are a lot of processing units, as listed below:</p>\r\n <ul>\r\n <li class="gmail-q-text gmail-qu-display--block">Processors Taxonomy</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Central Processing Unit (CPU). If designed conforming to the von Neumann architecture, containing at least a control unit (CU), arithmetic logic unit (ALU) and processor registers.</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Graphics Processing Unit (GPU)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Sound chips and sound cards</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Vision Processing Unit (VPU)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Tensor Processing Unit (TPU)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Neural Processing Unit (NPU)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Physics Processing Unit (PPU)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Digital Signal Processor (DSP)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Image Signal Processor (ISP)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Synergistic Processing Element or Unit (SPE or SPU) in the cell microprocessor</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Field-Programmable Gate Array (FPGA)</li>\r\n <li class="gmail-q-text gmail-qu-display--block">Quantum Processing Unit (QPU)</li>\r\n </ul>\r\n <p class="gmail-q-text gmail-qu-display--block">A Graphical Processing Unit (GPU) enables you to run high-definition graphics on your computer. GPU has hundreds of cores aligned in a particular way forming a single hardware unit. It has thousands of concurrent hardware threads, utilized for data-parallel and computationally intensive portions of an algorithm. Data-parallel algorithms are well suited for such devices because the hardware can be classified as SIMT (Single Instruction Multiple Threads). GPUs outperform CPUs in terms of GFLOPS.</p>\r\n <h2 class="gmail-q-text gmail-qu-display--block">From Fake AI Accelerators ASIC to Real AI Accelerators</h2>\r\n <p class="gmail-q-text gmail-qu-display--block">The TPU and NPU go under a Narrow/Weak AI/ML/DL accelerator class of specialized hardware accelerator or computer system designed to accelerate special AI/ML applications, including artificial neural networks and machine vision.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">Big-Tech companies such as Google, Amazon, Apple, Facebook, AMD and Samsung are all designing their own AI ASICs.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">Typical applications include algorithms for training and inference in computing devices, such as self-driving cars, machine vision, NLP, robotics, internet of things, and other data-intensive or sensor-driven tasks. They are often manycore designs and generally focus on low-precision arithmetic, novel dataflow architectures or in-memory computing capability, with a typical NAI integrated circuit chip containing billions of MOSFET transistors.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">Focus on training and inference of deep neural networks, Tensorflow uses a symbolic math library based on dataflow and differentiable programming</p>\r\n <p class="gmail-q-text gmail-qu-display--block">The former uses automatic differentiation (AD), algorithmic differentiation, computational differentiation, or auto-diff, and gradient-based optimization, working by constructing a graph containing the control flow and data structures in the program.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">Again, the datastream/dataflow programming is a programming paradigm that models a program as a directed graph of the data flowing between operations, thus implementing data flow principles and architecture.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">Things revolve around static or dynamic graphs, requesting the proper programming languages, such as C++, Python, R, or Julia, and ML libraries, such as TensorFlow or PyTorch.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">What AI computing is still missing is a Causal Processing Unit, involving symmetrical causal data graphs, with the Causal Engine software simulating real-world phenomena in digital reality.</p>\r\n <p class="gmail-q-text gmail-qu-display--block">It is highly likely embedded in the human brain and Real-World AI.</p> """ -user: Proxies\__CG__\App\Entity\User {#1092 …} -createdAt: DateTime @1630511111 {#1145 : 2021-09-01 15:45:11.0 UTC (+00:00) } -updatedAt: DateTime @1630533673 {#1150 : 2021-09-01 22:01:13.0 UTC (+00:00) } -deletedAt: null -category: App\Entity\Category {#445 …} -status: "published" -imageCard: Proxies\__CG__\App\Entity\File {#1184 …} -ImageHeader: Proxies\__CG__\App\Entity\File {#1184 …} -featured: false -mainView: false -clicks: 7335 -comments: Doctrine\ORM\PersistentCollection {#1125 …} -reviewed_at: DateTime @1630511111 {#1148 : 2021-09-01 15:45:11.0 UTC (+00:00) } -metakey: "Are The Highly-Marketed Deep Learning and Machine Learning Processors Just Simple Matrix-Multiplication Accelerators?" -metadesc: "Most AI accelerators are just simple data matrix-multiplication accelerators. All the rest is commercial propaganda." -robots: null -publishedAt: DateTime @1630511111 {#1147 : 2021-09-01 15:45:11.0 UTC (+00:00) } -canonical: null -superTag: null } |
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