Posts Tagged ‘FinFET’

IBM Resurrects Moore’s Law

June 23, 2017

Guess Moore’s Law ain’t as dead as we were led to believe. On Jun 5 IBM and Research Alliance partners GLOBALFOUNDRIES and Samsung, along with equipment suppliers announced the development of an industry-first process to build silicon nano sheet transistors that will enable 5nm chips. Previously, IBM announced a 7nm process using a silicon germanium (SiGe) alloy.

As DancingDinosaur wrote in early Oct. 2015, the last z System that conformed to the expectations of Moore’s Law was the zEC12, introduced Aug 2012. IBM could boast then it had the fastest commercial processor available.  The subsequent z13 didn’t match it in processor speed.  The z13 chip runs a 22 nm core at 5 GHz, one-half a GHz slower than the zEC12, which ran its 32nm core at 5.5 GHz. IBM compensated for the slower chip speed by adding more processors throughout the system to boost I/O and other functions and optimizing the box every way possible.

5nm silicon nano-sheet transistors delivers 40% performance gain

By 2015, the z13 delivered about a 10 percent performance bump per core thanks to the latest tweaks in the core design, such as better branch prediction and better pipelining. But even at one-half Ghz slower, the z13 was the first system to process 2.5 billion transactions a day.  Even more importantly for enterprise data centers, z13 transactions are persistent, protected, and auditable from end-to-end, adding assurance as mobile transactions grow to an estimated 40 trillion mobile transactions per day by 2025. The z13 also received and continues to receive praise for its industry leading security ratings as well as its scalability and flexibility.

Just recently Hitachi announced a partnership with IBM to develop a version of the z13 to run its own operating system, VOS3. The resulting z13 will run the next generation of Hitachi’s AP series.

But IBM isn’t back in pursuit of Moore’s Law just to deliver faster traditional mainframe workloads. Rather, the company is being driven by its strategic initiatives, mainly cognitive computing. As IBM explained in the announcement: The resulting increase in performance will help accelerate cognitive computing, the Internet of Things (IoT), and other data-intensive applications delivered in the cloud. The power savings could also mean that the batteries in smartphones and other mobile products could last two to three times longer than today’s devices, before needing to be charged.

Scientists working as part of the IBM-led Research Alliance at the SUNY Polytechnic Institute Colleges of Nanoscale Science and Engineering’s NanoTech Complex in Albany, NY achieved the breakthrough by using stacks of silicon nanosheets as the device structure of the transistor instead of the standard FinFET architecture, which is the blueprint for the semiconductor industry up through 7nm node technology. “For business and society to meet the demands of cognitive and cloud computing in the coming years, advancement in semiconductor technology is essential,” said Arvind Krishna, senior vice president, Hybrid Cloud, and director, IBM Research in the announcement. “That’s why IBM aggressively pursues new and different architectures and materials that push the limits of this industry, and brings them to market in technologies like mainframes and our cognitive systems.”

Compared to the leading edge 10nm technology available in the market, according to IBM, a nanosheet-based 5nm technology can deliver 40 percent performance enhancement at fixed power, or 75 percent power savings at matched performance. This improvement enables a significant boost to meeting the future demands of artificial intelligence (AI) systems, virtual reality, and mobile devices.

These may not sound like the workloads you are running on your mainframe now, but systems with these chips are not going to be shipped in the next mainframe either. So, you have a couple of years. The IBM team expects to make progress toward commercializing 7nm in 2018. By the time they start shipping 5nm systems you might be desperate for a machine to run such workloads and others like them.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.


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