{"id":1904,"date":"2023-07-03T05:48:17","date_gmt":"2023-07-03T02:48:17","guid":{"rendered":"https:\/\/aivolga.com\/?page_id=1904"},"modified":"2023-08-08T08:49:44","modified_gmt":"2023-08-08T05:49:44","slug":"analog-computing","status":"publish","type":"page","link":"https:\/\/aivolga.com\/?page_id=1904","title":{"rendered":"Analog Computing"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"1904\" class=\"elementor elementor-1904\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-6dd091be elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"6dd091be\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;shape_divider_bottom&quot;:&quot;tilt&quot;,&quot;ekit_has_onepagescroll_dot&quot;:&quot;yes&quot;}\">\n\t\t\t\t\t\t\t<div class=\"elementor-background-overlay\"><\/div>\n\t\t\t\t\t\t<div class=\"elementor-shape elementor-shape-bottom\" aria-hidden=\"true\" data-negative=\"false\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 1000 100\" preserveAspectRatio=\"none\">\n\t<path class=\"elementor-shape-fill\" d=\"M0,6V0h1000v100L0,6z\"\/>\n<\/svg>\t\t<\/div>\n\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-698300c3 elementor-invisible\" data-id=\"698300c3\" data-element_type=\"column\" data-e-type=\"column\" data-settings=\"{&quot;animation&quot;:&quot;fadeInLeft&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-67b6d351 elementor-widget elementor-widget-heading\" data-id=\"67b6d351\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;ekit_we_effect_on&quot;:&quot;none&quot;}\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\"><span style=\"color:#12b39b\">Analog Computing<\/span><br>Achieving unmatched efficiency and performance<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-60c6d07 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"60c6d07\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;ekit_has_onepagescroll_dot&quot;:&quot;yes&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-d8245ea\" data-id=\"d8245ea\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1bac837 elementor-widget elementor-widget-image\" data-id=\"1bac837\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;ekit_we_effect_on&quot;:&quot;none&quot;}\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/aivolga.com\/wp-content\/uploads\/2023\/07\/DAC_ADC.png\" title=\"DAC_ADC\" alt=\"DAC_ADC\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-d243f7f\" data-id=\"d243f7f\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ac41ed1 elementor-widget elementor-widget-text-editor\" data-id=\"ac41ed1\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;ekit_we_effect_on&quot;:&quot;none&quot;}\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Analog computing provides the ultimate compute-in-memory processing element. The term compute-in-memory is used very broadly and can mean many things. Our analog compute takes compute-in-memory to an extreme, where we compute directly inside the memory array itself. This is possible by using the memory elements as tunable resistors, supplying the inputs as voltages, and collecting the outputs as currents. We use analog computing for our core neural network matrix operations, where we are multiplying an input vector by a weight matrix.<\/p><p>Analog computing provides several key advantages. First, it is amazingly efficient; it eliminates memory movement for the neural network weights since they are used in place as resistors. Second, it is high performance; there are hundreds of thousands of multiply-accumulate operations occurring in parallel when we perform one of these vector operations. Given these two properties, analog computing is the core of our high-performance yet highly-efficient system.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-326708f elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"326708f\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;ekit_has_onepagescroll_dot&quot;:&quot;yes&quot;}\">\n\t\t\t\t\t\t\t<div class=\"elementor-background-overlay\"><\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-98dd98e\" data-id=\"98dd98e\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap\">\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Analog ComputingAchieving unmatched efficiency and performance Analog computing provides the ultimate compute-in-memory processing element. The term compute-in-memory is used very broadly and can mean many things. Our analog compute takes compute-in-memory to an extreme, where we compute directly inside the memory array itself. This is possible by using the memory elements as tunable resistors, supplying [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":887,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"footnotes":""},"class_list":["post-1904","page","type-page","status-publish","hentry"],"lang":"en","translations":{"en":1904,"ru":1965},"pll_sync_post":[],"_links":{"self":[{"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/pages\/1904","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aivolga.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1904"}],"version-history":[{"count":21,"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/pages\/1904\/revisions"}],"predecessor-version":[{"id":3247,"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/pages\/1904\/revisions\/3247"}],"up":[{"embeddable":true,"href":"https:\/\/aivolga.com\/index.php?rest_route=\/wp\/v2\/pages\/887"}],"wp:attachment":[{"href":"https:\/\/aivolga.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1904"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}