EXTENDING THE LIMITS OF MAGNETIC RECORDING

September 8, 2000

SCIENCE & ENGINEERING NEWS

San Diego, CALIF. — Digital magnetic recording is the central technology of information storage. Magnetic recording systems include the storage media (disks and tapes) and the transducers that write and read information: the record and playback heads. Disks, for example, are layered structures of thin films of cobalt-based crystals, in which the density of the stored information depends largely on the size of the grains in the coating. The smaller the grains, the more bits can be recorded in a given area. As grain sizes have become smaller, the capacity of hard disk drives has doubled annually for the past few years. But when bits are written on tinier and tinier grains, the stored information is eventually subject to thermal instability – a tiny kick in energy can change a “1” to a “0.”

UC San Diego scientist H. Neal Bertram and colleagues, in collaboration with SDSC staff, are exploring models of computer disks to determine the thermal stability limits for ultrahigh-density systems with extremely fine grains. Their work is stretching the capacity of the Sun HPC 10000 at SDSC.

“Our group focuses on the fundamental physics of magnetic recording,” said Bertram, professor of electrical and computer engineering, who holds an Endowed Chair in the Center for Magnetic Recording Research (CMRR) at UC San Diego. “We use sophisticated, computationally intensive models to simulate the recording process in advanced devices, taking into account a variety of variables, from short- and long-range interactions among grains to inhomogeneities in grain microstructure that affect recording results.”

The CMRR was founded on the UC San Diego campus in 1983 by a consortium of 12 U.S. companies in the magnetic recording industry. Bertram and his students have used SDSC resources since 1986. “Now we are on the threshold of a great increase in the size and power of our calculations,” Bertram said, “thanks to massively parallel computation and our collaboration with the computational scientists at SDSC.”

The group has used supercomputing resources to analyze the time evolution of recording on disks. Most current disk technologies employ longitudinal recording, with the magnetization direction of each grain in the plane of the medium. However, perpendicular recording, with the magnetization aligned vertically to the disk surface, may be coming into use and is currently under serious investigation by all the major disk drive companies. Perpendicular recording appears capable of main taining good signal-to-noise ratio and thermal stability at higher densities. Another candidate is patterned media, in which each bit is assigned to an individual grain. “We have used our codes to analyze all types of media,” said Bertram, who has been an IEEE Distinguished Lecturer and is the author of Theory of Magnetic Recording (Cambridge University Press, 1994).

Current disk technology permits areal densities of tens of gigabits per square inch, which can be recorded or read out at rates as high as 200 MHz. The industry’s next objective is to go an order of magnitude higher in density and speed, with hundreds of gigabits per square inch readable at gigahertz rates. Ideally, new media should exhibit the same 10-year thermal stability at room temperature as current media.

In modeling the stability of magnetic disk media, Neal Bertram and Hong Zhou simulated the difference between two states of affairs. Above is a representation of the medium at the beginning of a run on the Sun HPC 10000 at SDSC. Red and blue colors represent two magnetization directions. The thermal decay was exaggerated slightly to get this contrast. At the start of the simulation, bit striping is clearly evident.

Recently, as part of an NPACI Strategic Applications Collaboration (SAC) project, Amitava Majumdar of the SDSC Scientific Computing Department worked with Hong Zhou, Bertram’s graduate student, on a simulation of thermal instability in dense disk media, using smaller and smaller grain sizes.

“As the volume of each grain decreases, the amount of energy needed to reverse the direction of magnetization also becomes smaller,” Zhou said. “We use a Monte Carlo method to randomly distribute and change magnetization directions for an assembly of grains and calculate the probability that such changes will occur within a given time – from a nanosecond to 10 years.”

Typically, the medium is represented as a 128 x 128 array of hexagons. A single run typically involves 120 calculations with varying random properties (grain orientations) to determine medium noise and thus the system’s signal-to-noise ratio. When the collaboration began, Zhou was obtaining a speed of about 250 Mflops on a single processor of the Cray T90 at SDSC.

“But a single run on one such processor took about 18 hours of processor time,” Majumdar said. “Our analysis indicated that the code might perform very efficiently on the Sun HPC 10000.” The HPC 10000 is a parallel machine with 64 processors and 64 GB of shared memory uniformly accessible from each processor. Majumdar and Zhou developed an implementation of the code using the Message-Passing Interface (MPI) library that was parallel across the initial conditions. “With this change and a number of smaller improvements in the code, the run time on 40 processors of the Sun was reduced to 2.5 hours. The parallel code scales almost linearly, since initial conditions can be simulated independently of one another.”

“That speedup alone is very important for us,” Zhou said. “Professor Bertram and I can now test more initial conditions, since the code is parallel, and we can increase the size of our simulation, because of the large memory of the HPC 10000, to represent higher areal bit densities.” Majumdar and Zhou have further improved the code by finding and linking mathematical libraries for parallel random number generation. “We are also investigating changes in the Monte Carlo code that may reduce the variance and thus help to simulate more realistic problems faster,” Majumdar said.

SAC program coordinator Bob Sinkovits and SDSC scientist Stuart Johnson have begun work with another Bertram student, Chris Seberino, on the group’s code for analyzing tape recording. “The main part of this code is an implementation of the Fast Multipole Method,” Johnson said. “We are adapting an efficient parallel implementation of this method that was already in use by scientists in another area of physics entirely.”

Sinkovits pointed out that the ability of the SAC team to improve the efficiencies of major codes benefits from the synergies implicit in working across multiple disciplines. “We become code mavens – people with a kind of expertise rarely developed in academic groups within a single discipline,” he said. “The more experience our group has with this kind of work, the better our unique form of collaboration becomes, for all kinds of science.” For example, NPACI has a range of high-end machines with architectures and protocols that differ. One code with certain demands on machine memory may run better on the Sun HPC 10000 than the IBM SP machines; another, with differing characteristics, may run better on one of the SP configurations.

“I am very much impressed with what the SDSC computational scientists have been able to do with our codes,” Bertram said. “We’ve been given some new handles on our ever-changing problems that can increase our power to predict and guide the way forward for a vital technology.”

============================================================

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!

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

Nvidia Appoints Andy Grant as EMEA Director of Supercomputing, Higher Education, and AI

March 22, 2024

Nvidia recently appointed Andy Grant as Director, Supercomputing, Higher Education, and AI for Europe, the Middle East, and Africa (EMEA). With over 25 years of high-performance computing (HPC) experience, Grant brings a Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen 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…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. 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…

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…

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…

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…

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…

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…

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…

Leading Solution Providers

Contributors

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…

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…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer 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…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire