{"id":70285,"date":"2017-06-07T22:07:56","date_gmt":"2017-06-08T05:07:56","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2017\/06\/ibm-squeezes-30-billion-transistors-into-a-fingernail-sized-chip"},"modified":"2017-06-07T22:07:56","modified_gmt":"2017-06-08T05:07:56","slug":"ibm-squeezes-30-billion-transistors-into-a-fingernail-sized-chip","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2017\/06\/ibm-squeezes-30-billion-transistors-into-a-fingernail-sized-chip","title":{"rendered":"IBM squeezes 30 billion transistors into a fingernail-sized chip"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/ibm-squeezes-30-billion-transistors-into-a-fingernail-sized-chip.jpeg\"><\/a><\/p>\n<p>Who said <a href=\"https:\/\/www.engadget.com\/2015\/07\/16\/intel-skylake-chips-delayed\/\">Moore\u2019s Law<\/a> was dead? Certainly not IBM or its chip partners Globalfoundries and Samsung. The trio has developed a transistor manufacturing process that should pave the way for <a href=\"https:\/\/www.engadget.com\/2012\/05\/14\/intel-sets-sights-on-5nm-chip\/\">5-nanometer chips<\/a>. While the team etched the chip using the same extreme ultraviolet lithography (EUV) used for the breakthrough <a href=\"https:\/\/www.engadget.com\/2015\/07\/09\/IBM-7nm-chip\/\">7nm chip<\/a>, it ditched the common <a href=\"https:\/\/www.engadget.com\/2013\/04\/12\/tsmc-narrows-production-of-16nm-finfet-chips-to-late-2013\/\">FinFET<\/a> (fin field effect) transistor design in favor of stacks of silicon nanosheets. The switch makes it possible to fine-tune individual circuits to maximize their performance as they\u2019re crammed into an incredibly small space. How small? At 5nm, the group says it can squeeze 30 billion transistors into a chip the size of a fingernail (see below) \u2014 not bad when the 7nm chip held 20 billion transistors a couple of years ago.<\/p>\n<p>IBM sees the technique helping its own <a href=\"https:\/\/www.engadget.com\/2017\/04\/07\/ibm-watson-tech-support-round-the-clock\/\">cognitive computing efforts<\/a> as well as the Internet of Things and other \u201cdata-intensive\u201d tasks. However, it\u2019s also painting a rosy picture for the future of mobile devices \u2014 it imagines phones having \u201ctwo to three times\u201d more battery life than <a href=\"https:\/\/www.engadget.com\/2016\/11\/17\/qualcomm-snapdragon-835-fast-charging\/\">current devices<\/a>. That\u2019s likely optimistic (phone makers tend to focus on speed over longevity), but it won\u2019t be shocking if future hardware is both faster and wrings out a little more from every charge.<\/p>\n<p>Just don\u2019t expect to see real-world examples of this for a while. We haven\u2019t even seen devices shipping with 7nm chips (they\u2019re not expected until 2018 at the earliest), so it could easily be a couple of years or more before 5nm arrives. Still, that 5nm is even on the roadmap is important. Chip designers won\u2019t have to reinvent the wheel to get meaningful improvements, and you won\u2019t have to worry about device performance growing stale for at least the next few years.<\/p>\n<p><!-- Link: <a href=\"https:\/\/www.engadget.com\/2017\/06\/05\/ibm-5nm-chip-manufacturing\/\">https:\/\/www.engadget.com\/2017\/06\/05\/ibm-5nm-chip-manufacturing\/<\/a> --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Who said Moore\u2019s Law was dead? Certainly not IBM or its chip partners Globalfoundries and Samsung. The trio has developed a transistor manufacturing process that should pave the way for 5-nanometer chips. While the team etched the chip using the same extreme ultraviolet lithography (EUV) used for the breakthrough 7nm chip, it ditched the common [\u2026]<\/p>\n","protected":false},"author":367,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1523,418,1512,47],"tags":[],"class_list":["post-70285","post","type-post","status-publish","format-standard","hentry","category-computing","category-internet","category-mobile-phones","category-neuroscience"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/70285","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/367"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=70285"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/70285\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=70285"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=70285"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=70285"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}