{"id":150708,"date":"2023-09-06T13:34:45","date_gmt":"2023-09-06T08:04:45","guid":{"rendered":"https:\/\/dripp.zone\/news\/?p=150708"},"modified":"2023-09-06T13:34:45","modified_gmt":"2023-09-06T08:04:45","slug":"microsoft-boosts-ai-efficiency-with-a-heavy-metal-quartet-of-compilers-crypto-news","status":"publish","type":"post","link":"https:\/\/dripp.zone\/news\/microsoft-boosts-ai-efficiency-with-a-heavy-metal-quartet-of-compilers-crypto-news\/","title":{"rendered":"Microsoft Boosts AI Efficiency With a \u2018Heavy Metal Quartet\u2019 of Compilers &#8211; Crypto News"},"content":{"rendered":"<div style=\"position:relative;overflow:visible;font-size:1.2em;line-height:1.58\">\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">Microsoft has unveiled a suite of four new artificial intelligence compilers designed to optimize the performance of various AI models. The \u201cheavy metal quartet\u201d of cutting-edge compilation tools bear the names Rammer, Roller, Welder and Grinder.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The tools were developed by Microsoft Research in collaboration with a number of academic institutions. They provide advanced solutions for compiling \u2014basically the transformation from source code (human readable) into machine code (a bunch of ones and zeroes that make a computer executable)\u2014 mainstream AI models and running them more efficiently on hardware accelerators like GPUs.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">In a Microsoft Research <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/blog\/building-a-heavy-metal-quartet-of-ai-compilers\/\" class=\"sc-adb616fe-0 ePvUAp\">blog post<\/a> highlighting their capabilities, the company says the compilers build on Microsoft&#8217;s extensive research and development in artificial intelligence.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">\u201cThe AI compilers we developed have demonstrated a substantial improvement in AI compilation efficiency, thereby facilitating the training and deployment of AI models,\u201d wrote \u200b\u200bJilong Xue, Principal Researcher at MSR Asia. \u201cIn the future, these large-scale models themselves may inherently assist in achieving optimization and compilation.\u201d<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The four new compilers each tackle distinct challenges in optimizing AI workloads.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\"><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/rammer-enabling-holistic-deep-learning-compiler-optimizations-with-rtasks\/\" class=\"sc-adb616fe-0 ePvUAp\">Rammer<\/a> focuses on maximizing hardware parallelism\u2014the capacity of hardware to do different things simoultaneously. This is a key factor in performance, and Rammer minimizes runtime scheduling overhead through improved utilization of parallel resources.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\"><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/roller-fast-and-efficient-tensor-compilation-for-deep-learning\/\" class=\"sc-adb616fe-0 ePvUAp\">Roller<\/a> takes a different approach to accelerate compilation, using a fast construction algorithm to find solutions, ultimately generating optimized kernels in seconds rather than hours. In other words, Roller helps create efficient computer programs for AI faster by simplifying the design process.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\"><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/welder-scheduling-deep-learning-memory-access-via-tile-graph\/\" class=\"sc-adb616fe-0 ePvUAp\">Welder<\/a> reduces expensive memory access traffic by connecting operators in a concentrated pipeline. It unifies memory optimizations into a single framework for greater efficiency.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">Finally, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.microsoft.com\/en-us\/research\/publication\/cocktailer-analyzing-and-optimizing-dynamic-control-flow-in-deep-learning\/\" class=\"sc-adb616fe-0 ePvUAp\">Grinder<\/a> enables control-flow execution on accelerators by integrating it with data flow. This allows optimization across control flow boundaries. Think of it like an expert guiding the steps of an apprentice, telling them what to do to get the job done faster.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">As one of the leading technology giants, Microsoft has been at the forefront of AI advancement. The company has partnered closely with AI research firm OpenAI on large language models like GPT-3.5 and GPT-4, which powers ChatGPT and Bing Chat. More recently, Microsoft <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/decrypt.co\/149076\/microsoft-meta-llama-azure-partnership\" class=\"sc-adb616fe-0 ePvUAp\">partnered with Meta<\/a> to integrate LLaMA-2 in its cloud computing solution and introduced a technique called the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/decrypt.co\/154073\/microsoft-infuses-ai-with-human-like-reasoning-via-an-algorithm-of-thoughts\" class=\"sc-adb616fe-0 ePvUAp\">Algorithm of Thoughts<\/a> to enhance reasoning in models like ChatGPT.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">Testing found the compilers significantly outperformed existing solutions on benchmarks. Rammer exceeded other compilers by up to 20x on GPUs. Roller matched or exceeded state-of-the-art performance while lowering compilation time by orders of magnitude. Welder surpassed frameworks like PyTorch by up to 21x on GPUs. Grinder accelerated models with control flow by up to 8x.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">The heavy metal quartet demonstrates Microsoft\u2019s continued leadership in designing breakthrough AI systems \u2014and coming up with fun names for its products. While big partnerships in the AI space like the one with OpenAI <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/blogs.microsoft.com\/blog\/2023\/01\/23\/microsoftandopenaiextendpartnership\/\" class=\"sc-adb616fe-0 ePvUAp\">grab headlines<\/a>, the company also actively develops vital software infrastructure to empower AI behind the scenes.<\/p>\n<p class=\"font-meta-serif-pro scene:font-noto-sans scene:text-base scene:md:text-lg font-normal text-lg md:text-xl md:leading-9 tracking-px text-body gg-dark:text-neutral-100\">With sizable performance gains over existing solutions, Rammer, Roller, Welder and Grinder could provide key competitive advantages as more complex AI workloads emerge.<\/p>\n<div class=\"my-4 border-b border-decryptGridline\">\n<div class=\"text-left p-8 md:py-12 md:px-12 max-w-prose relative\"><span class=\"border-t-4 border-l-4 w-4 h-4 md:border-t-[6px] md:border-l-[6px] md:w-6 md:h-6 border-decryptPurple dark:border-decryptNeon gg-dark:border-cc-pink-2 absolute top-4 left-4 md:top-6 md:left-6\" \/><span class=\"border-t-4 border-l-4 w-4 h-4 md:border-t-[6px] md:border-l-[6px] md:w-6 md:h-6 border-decryptPurple dark:border-decryptNeon gg-dark:border-cc-pink-2 absolute rotate-180 bottom-4 right-4 md:bottom-6 md:right-6\" \/><\/p>\n<h3 class=\"font-akzidenz-grotesk font-bold text-xl md:text-3xl mb-6 md:text-center gg-dark:text-white\">Stay on top of crypto news, get daily updates in your inbox.<\/h3>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Microsoft has unveiled a suite of four new artificial intelligence compilers designed to optimize the performance of various AI models. The \u201cheavy metal quartet\u201d of cutting-edge compilation tools bear the names Rammer, Roller, Welder and Grinder. The tools were developed by Microsoft Research in collaboration with a number of academic institutions. They provide advanced solutions [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":150709,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[5],"tags":[230,225,221,227,226,228,229,60,223,224,222],"class_list":["post-150708","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-cryptocurrency","tag-brave","tag-coinbase","tag-crypto","tag-decentralised","tag-decentralized","tag-decentralized-exchange","tag-erc-20","tag-featured","tag-meme-coin","tag-robinhood","tag-solana"],"_links":{"self":[{"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/posts\/150708","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/comments?post=150708"}],"version-history":[{"count":2,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/posts\/150708\/revisions"}],"predecessor-version":[{"id":150711,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/posts\/150708\/revisions\/150711"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/media\/150709"}],"wp:attachment":[{"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/media?parent=150708"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/categories?post=150708"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dripp.zone\/news\/wp-json\/wp\/v2\/tags?post=150708"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}