IBM is investing $3bn over the next 5 years in two broad research and early-stage development programs to push the limits of chip technology needed to meet the emerging demands of cloud computing and ‘big data’ systems.
The first program is aimed at ‘7nm and beyond’ silicon technology that will address physical challenges that are threatening existing semiconductor scaling techniques and will impede the ability to manufacture such chips. The second is focused on developing alternative technologies for post-silicon-era chips using entirely different approaches, necessitated because of the physical limitations of silicon-based semiconductors.
Cloud and big-data applications are placing new challenges on systems, just as the underlying chip technology is facing significant physical scaling limits, says IBM. Bandwidth to memory, high-speed communication and device power consumption are becoming increasingly challenging and critical.
The teams will comprise IBM Research scientists and engineers from Albany and Yorktown, NY; Almaden, CA; and Europe. In particular, IBM will be investing in emerging areas of research that are already underway such as carbon nanoelectronics, silicon photonics, new memory technologies, and architectures that support quantum and cognitive computing.
The teams will focus on providing orders-of-magnitude improvement in system-level performance and energy-efficient computing. In addition, IBM will continue to invest in nanosciences and quantum computing - two areas of fundamental science where it has remained a pioneer for over three decades.
7nm technology and beyond
Although it is challenging, semiconductors show promise to scale from existing 22nm dimensions down to 14nm and then 10nm in the next several years. However, scaling to 7nm and perhaps below by the end of the decade will require significant investment and innovation in semiconductor architectures as well as the invention of new tools and techniques for manufacturing, says IBM.
IBM and its partners are already working on the materials science and device engineering required to meet the demands of the emerging system requirements for cloud, big data, and cognitive systems, says John Kelly, senior vice president, IBM Research.
“Scaling to 7nm and below is a terrific challenge, calling for deep physics competencies in processing nano materials affinities and characteristics,” comments Richard Doherty, technology research director, The Envisioneering Group. “IBM is one of a very few companies who has repeatedly demonstrated this level of science and engineering expertise.”
Bridge to a ‘post-silicon’ era
Beyond 7nm, the challenges dramatically increase, requiring a new kind of material to power systems of the future, and new computing platforms to solve problems that are unsolvable or difficult to solve today, says IBM. Potential alternatives include new materials such as carbon nanotubes, and non-traditional computational approaches such as neuromorphic computing, cognitive computing, machine learning techniques, and the science behind quantum computing.
IBM holds over 500 patents for technologies that it says will drive advancements at 7nm and beyond silicon. These continued investments aim to accelerate the invention and introduction into product development for IBM's computing systems for cloud and big-data analytics.
IBM reckons that exploratory research that could lead to major advancements in delivering much smaller, faster and more powerful computer chips include quantum computing, neurosynaptic computing, silicon photonics, carbon nanotubes, III-V technologies, low-power transistors and graphene:
Silicon photonics
For over 12 years, IBM has been developing CMOS integrated silicon photonics technology, which integrates functions for optical communications on a silicon chip. The IBM team has recently designed and fabricated the first monolithic silicon photonics based transceiver with wavelength division multiplexing (WDM). Such transceivers will use light to transmit data between different components in a computing system at high data rates, low cost, and in an energetically efficient manner, says the firm.
Silicon nanophotonics can provide a super highway for large volumes of data to move at rapid speeds between computer chips in servers, large data-centers, and supercomputers, alleviating the limitations of congested data traffic and high-cost traditional interconnects.
Businesses are entering a new era of computing that requires systems to process and analyze, in real-time, huge volumes of information (‘big data’), notes IBM. Silicon nanophotonics can provide answers to big-data challenges by seamlessly connecting various parts of large systems, whether a few centimeters or few kilometers apart, and move terabytes of data via pulses of light through optical fibers, adds the firm.
III-V technologies
IBM has demonstrated what is claimed to be the highest transconductance on a self-aligned III-V channel metal-oxide semiconductor (MOS) field-effect transistors (FETs) device structure that is compatible with CMOS scaling. These materials and structural innovation are expected to pave the way for technology scaling at 7nm and beyond. With more than an order of magnitude higher electron mobility than silicon, integrating III-V materials into CMOS enables higher performance at lower power density, allowing for an extension to power/performance scaling to meet the demands of cloud computing and big-data systems, says IBM.
Carbon nanotubes
IBM researchers are also working on carbon nanotube (CNT) electronics and exploring whether CNTs can replace silicon beyond the 7nm node. As part of its activities for developing carbon nanotube based CMOS VLSI circuits, IBM recently demonstrated the first 2-way CMOS NAND gates using 50nm-gate-length CNT transistors.
IBM also has demonstrated the capability for purifying carbon nanotubes to 99.99% - the highest (verified) purities demonstrated to date - and transistors at 10nm channel length that show no degradation due to scaling; this is unmatched by any other material system to date, notes IBM.
Carbon nanotubes (single atomic sheets of carbon rolled up into a tube) form the core of a transistor device that will work in a fashion similar to the existing silicon transistor but can perform better, says IBM. They could be used to replace the transistors in chips that power data-crunching servers, high-performing computers and ultra-fast smart phones.
CNT transistors can operate as excellent switches at molecular dimensions of less than 10nm – less than half the size of the leading silicon technology. Comprehensive modeling of the electronic circuits suggests that about a performance improvement of 5-10 times compared to silicon circuits is possible.
Graphene
Graphene (pure carbon in the form of a sheet just one atomic layer thick) is an excellent conductor of heat and electricity, and is also remarkably strong and flexible. Electrons can move in graphene about ten times faster than in commonly used semiconductor materials such as silicon and silicon germanium (SiGe). Its characteristics offer the possibility to build faster switching transistors than are possible with conventional semiconductors, particularly for applications in handheld wireless communications, where it can be a more efficient switch than those currently used.
Recently in 2013, IBM demonstrated the first grapheme-based integrated circuit receiver front-end for wireless communications (consisting of a 2-stage amplifier and a down-converter operating at 4.3GHz).
Next-generation low-power transistors
In addition to new materials like CNTs, new architectures and innovative device concepts are required to boost future system performance, says IBM. Power dissipation is a fundamental challenge for nanoelectronic circuits. In existing transistors, energy is constantly leaking in the off-state.
A potential alternative to today’s power-hungry silicon field-effect transistors (FETs) are steep-slope devices, which could operate at much lower voltage and thus dissipate significantly less power. IBM is researching tunnel field-effect transistors (TFETs) in which the quantum-mechanical effect of band-to-band tunneling is used to drive the flow of current through the transistor. TFETs could achieve a 100-fold power reduction over CMOS transistors, so integrating TFETs with CMOS technology could improve low-power ICs.
Recently, IBM has developed a novel method to integrate III-V nanowires and heterostructures directly on standard silicon substrates and built the first InAs/Si tunnel diodes and TFETs using indium arsenide as the source and silicon as the channel with a wrap-around gate as a steep-slope device for low-power consumption applications.
“In the next ten years, computing hardware systems will be fundamentally different as our scientists and engineers push the limits of semiconductor innovations to explore the post-silicon future,” says Tom Rosamilia, senior vice president, IBM Systems and Technology Group. “IBM research and development teams are creating breakthrough innovations that will fuel the next era of computing systems.”
IBM’s contributions to silicon and semiconductor innovation include the invention and/or first implementation of: the single-cell DRAM, the ‘Dennard scaling laws’ underpinning Moore’s Law, chemically amplified photoresists, copper interconnect wiring, silicon-on-insulator (SOI), strained engineering, multi-core microprocessors, immersion lithography, high-speed silicon germanium (SiGe), high-k gate dielectrics, embedded DRAM, 3D chip stacking, and air-gap insulators.
IBM researchers are also credited with initiating the era of nano-devices following the Nobel prize winning invention of the scanning tunneling microscope (STM), which enabled nano- and atomic-scale innovation.
The firm says that it will also continue to fund and collaborate with university researchers to explore and develop future technologies for the semiconductor industry. In particular, IBM will continue to support and fund university research through private-public partnerships such as the NanoElectornics Research Initiative (NRI), and the Semiconductor Advanced Research Network (STARnet), and the Global Research Consortium (GRC) of the Semiconductor Research Corporation.
