IBM Clears Path to 5nm with Silicon Nanosheets

By Tiffany Trader

June 5, 2017

Two years since announcing the industry’s first 7nm node test chip, IBM and its research alliance partners GlobalFoundries and Samsung have developed a process to build 5 nanometer (nm) chips by combining a novel switch architecture with advanced lithography techniques.

The heart of the R&D advance is a new gate-all-around architecture that employs stacked silicon nanosheets, replacing the FinFET structure used in today’s leading processors. Instead of having one single vertical fin, the horizontal “stack” can send signals through four gates, providing for better leakage control at smaller scales.

IBM Research scientist Nicolas Loubet holds a wafer of chips with 5nm silicon nanosheet transistors (Photo Credit: Connie Zhou)

“We understood that the FinFET structure is running out of steam at 7nm and we had to invent a new device structure which could continue the scaling for several more generations,” said Mukesh V Khare, vice president at IBM Research, in an interview with HPCwire.

According to IBM, the gate-all-around architecture paves the way for fingernail-sized chips (~600mm2, says Khare) packed with 30 billion transistors—50 percent more transistors than IBM’s 7nm process enables. IBM estimates that this would provide close to a 40 percent improvement in performance for the same power or 75 percent power savings at matched performance compared with today’s leading-edge 10nm technology.

The same Extreme Ultraviolet (EUV) lithography approach that IBM used to produce the 7nm test node was applied to the nanosheet transistor architecture. With EUV, the width of the nanosheets can be adjusted continuously, within a single manufacturing process. “This adjustability permits the fine-tuning of performance and power for specific circuits – something not possible with today’s FinFET transistor architecture production,” says IBM.

IBM and its research partners have built the transistors on 300mm wafers. “We put the entire process together, measure, validate and then our partners get full access to the technology to take it from proof point with us at IBM to manufacturing,” said Khare.

Khare emphasized, “These are not one chip or one device types of proof point; these are put together on a manufacturing scale fab which is used for research by IBM Research alliance, so this is a realistic toolset, the toolset that will eventually mature into the manufacturing toolset.”

Market analyst Jim McGregor of Tirias Research did not hesitate to call this a credible advance. “There are basically three pillars of innovation in semiconductor manufacturing,” he said. “One is the lithography process, which we’ve been completely constrained on but we’re slowly moving to EUV. The second is materials technology, which we’ve been advancing rapidly over the past decade through string silicon and other chemical makeups and the third area is transistor design. That has remained stagnant for many years, a couple decades, until we went to FinFET over the past couple years, however FinFETs are going to have their limitations architecturally and this [advance] is addressing that limitation and allows us to continue scaling, and continue basically Moore’s law. It also is injecting new materials that are going to be critical going forward, such as the the nanosheets and nanowires.”

As promising as the technical merits may be here, however, we cannot forget the economic considerations of Moore’s law, said McGregor, which will likely leave semiconductor makers like GlobalFoundries looking to leverage the FinFET technology for as long as possible to recoup the major investments that it and its partners have made. “I would estimate that at 5nm you will still see traditional FinFET,” said McGregor, “You may see IBM’s nanosheet architecture creep in later on, maybe as a sub-node to 5nm or a following process.”

IBM Research has already completed its work on the 7nm process that it introduced two years ago and transferred the technology to its manufacturing partners. IBM has said that its 7nm node will be reaching “manufacturing maturity” towards end of this year, or early next year. “The technology is very, very close,” said Khare, “and the cycle continues with another breakthrough. We will continue to work with our manufacturing partners to make this technology fully available, eventually they will decide the right timing based both on business leads as well as market drivers.”

Like the 7nm test chip before it, the latest semiconductor proof point is part of IBM’s $3 billion, five-year investment in chip R&D that was announced in 2014. As a fundamental building block for semiconductor technology, node advances will benefit all those market segments that can benefit from silicon technology scale, including high-performance computing, enterprise, and mobile. IBM, not surprisingly, is particularly focused on enhancing its cognitive computing and cloud platforms.

“Although a lot of people think of Intel when they think of semiconductor advancements, you have to remember that IBM and their development consortium accounts for a vast amount of innovation in semiconductor processing over the past 15 years or so especially,” said McGregor. “I’d say almost half of the major innovations have probably come from that alliance. It also helps push that new technology into manufacturing because these companies work so close together.”

Feature image caption: A scan of IBM Research Alliance’s 5nm transistor, built using an industry-first process to stack silicon nanosheets as the device structure (Photo credit: IBM)

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Empowering High-Performance Computing for Artificial Intelligence

April 19, 2024

Artificial intelligence (AI) presents some of the most challenging demands in information technology, especially concerning computing power and data movement. As a result of these challenges, high-performance computing Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that have occurred about once a decade. With this in mind, the ISC Read more…

2024 Winter Classic: Texas Two Step

April 18, 2024

Texas Tech University. Their middle name is ‘tech’, so it’s no surprise that they’ve been fielding not one, but two teams in the last three Winter Classic cluster competitions. Their teams, dubbed Matador and Red Read more…

2024 Winter Classic: The Return of Team Fayetteville

April 18, 2024

Hailing from Fayetteville, NC, Fayetteville State University stayed under the radar in their first Winter Classic competition in 2022. Solid students for sure, but not a lot of HPC experience. All good. They didn’t Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use of Rigetti’s Novera 9-qubit QPU. The approach by a quantum Read more…

2024 Winter Classic: Meet Team Morehouse

April 17, 2024

Morehouse College? The university is well-known for their long list of illustrious graduates, the rigor of their academics, and the quality of the instruction. They were one of the first schools to sign up for the Winter Read more…

Kathy Yelick on Post-Exascale Challenges

April 18, 2024

With the exascale era underway, the HPC community is already turning its attention to zettascale computing, the next of the 1,000-fold performance leaps that ha Read more…

Software Specialist Horizon Quantum to Build First-of-a-Kind Hardware Testbed

April 18, 2024

Horizon Quantum Computing, a Singapore-based quantum software start-up, announced today it would build its own testbed of quantum computers, starting with use o Read more…

MLCommons Launches New AI Safety Benchmark Initiative

April 16, 2024

MLCommons, organizer of the popular MLPerf benchmarking exercises (training and inference), is starting a new effort to benchmark AI Safety, one of the most pre Read more…

Exciting Updates From Stanford HAI’s Seventh Annual AI Index Report

April 15, 2024

As the AI revolution marches on, it is vital to continually reassess how this technology is reshaping our world. To that end, researchers at Stanford’s Instit Read more…

Intel’s Vision Advantage: Chips Are Available Off-the-Shelf

April 11, 2024

The chip market is facing a crisis: chip development is now concentrated in the hands of the few. A confluence of events this week reminded us how few chips Read more…

The VC View: Quantonation’s Deep Dive into Funding Quantum Start-ups

April 11, 2024

Yesterday Quantonation — which promotes itself as a one-of-a-kind venture capital (VC) company specializing in quantum science and deep physics  — announce Read more…

Nvidia’s GTC Is the New Intel IDF

April 9, 2024

After many years, Nvidia's GPU Technology Conference (GTC) was back in person and has become the conference for those who care about semiconductors and AI. I Read more…

Google Announces Homegrown ARM-based CPUs 

April 9, 2024

Google sprang a surprise at the ongoing Google Next Cloud conference by introducing its own ARM-based CPU called Axion, which will be offered to customers in it Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Leading Solution Providers

Contributors

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Eyes on the Quantum Prize – D-Wave Says its Time is Now

January 30, 2024

Early quantum computing pioneer D-Wave again asserted – that at least for D-Wave – the commercial quantum era has begun. Speaking at its first in-person Ana Read more…

GenAI Having Major Impact on Data Culture, Survey Says

February 21, 2024

While 2023 was the year of GenAI, the adoption rates for GenAI did not match expectations. Most organizations are continuing to invest in GenAI but are yet to Read more…

The GenAI Datacenter Squeeze Is Here

February 1, 2024

The immediate effect of the GenAI GPU Squeeze was to reduce availability, either direct purchase or cloud access, increase cost, and push demand through the roof. A secondary issue has been developing over the last several years. Even though your organization secured several racks... Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire