Micron Exposes the Double Life of Memory with Automata Processor

By Nicole Hemsoth

November 22, 2013

If we had to take a pick from some of the most compelling announcements from SC13, the news from memory vendor (although that narrow distinction may soon change) Micron about its new Automata processor is at the top of the list. While at this point there’s still enough theory to lead us to file this under a technology to watch, the concept is unique in what it promises—both to Micron’s future and the accelerator/CPU space for some key HPC-oriented workloads.

In a nutshell, the Automata processor is a programmable silicon device that lends itself to handling high speed search and analysis across massive, complex, unstructured data. As an alternate processing engine for targeted areas, it taps into the inner parallelism inherent to memory to provide a robust and absolutely remarkable (if early benchmarks are to be believed) option for certain types of processing.

specs2

For starters, here’s what not to expect from Micron’s foray into the processor jungle. First, this is not something that will snap in to replace CPUs. Despite what some of the recent press elsewhere has described, these are a lot less like pure CPU competitors (at least at this point) and more like specialty accelerators (think FPGAs versus Xeons, for example).  These have been designed for a specific set of workloads, including network security, image processing, bioinformatics and select codes that propel the work of our three-letter overlords. The benefit here is that these are programmable, and in some ways reconfigurable and can chew on large-scale unstructured data analytics problems that the average conventional fixed word-width processors can’t always handle well.

Paul Dlugosch is director of Automata Processor Development in the Architecture Development Group of Micron’s DRAM division. “One thing people don’t understand well, aside from those memory researchers or people in this industry, is that any memory device is by nature a very highly parallel device. In fact, he says, “most of the power of that parallelism is left on the table and unused.”

He said that Micron has been stealthily developing their Automata technology for seven years—a process that was fed by a fundamental change in how they were thinking about memory’s role in large-scale systems. As Dlugosch told us, his company has been instrumental in rethinking memory with the Hybrid Memory Cube, but the memory wall needed some new ladders. The first rungs of which were those realizations that memory could be doing double-duty, so to speak.

At the beginning of their journey into automata territory, he said there were some fundamental questions about what caused the saturation of the memory interface and whether or not simply increasing bandwidth was the right approach. From there they started to think beyond the constraints of modern architectures in terms of how memory evolved in the first place.

Among the central questions are whether or not memory could be used as something other than a storage device. Further, the team set about investigating whether multicore concepts offered the shortest inroads to a high degree of parallelism. Also, they wondered if software that is comprised of sequential instructions and issued to an execution pipeline was a necessary component of systems or if there was a better way.

What’s most interesting about these lines of questioning is that his team started to realize that it might be possible that the memory wall was not erected because of memory bandwidth, but rather it was the symptom of a more profound root cause found elsewhere. That hidden weak point, said Dlugosch, is overall processor inefficiency. “What’s different about the automata processor is that rather than just trying to devise a means to transfer more information across a physical memory interface, we instead started asking why the mere need for high bandwidth is present.”

Micron Automata slide

The specs you see there are a bit difficult to make sense of since semiconductors aren’t often measured in this way. For example, placing value on how many path decisions can be made per second in a semiconductor device working on graph problems or executing non-deterministic finite automata is a bit esoteric, but even with a basic grasp consider that in one single Automata processor it has this capacity. And you’re not limited to one, either, since this is a scalable mechanism. The Automata director tells us that this is, in theory, as simple as adding more memory. In other words, one can put 8 Automata processors on a memory module–that memory module can then plug into a DIMM, and since you can have more than one it’s possible that it can scale this processing power just like memory.

What one can expect on the actual “real” use front is a fully developed SDK that will let end users compile automata and load those into the processor fabric, allowing them to execute as many automata in parallel against large datasets as the user can fit into one or more of the Automata processors. The idea here is that users will develop their own machines.

As one might imagine, however, the programming environment presents some significant challenges, but Micron is tapping into some of its early partners to make some inroads into this area. Their base low-level underpinnings are, as Dlugosch admitted, “not as expressive as we’d like it to be to get the full power from this chip,” but they’re working it via their own ANML (Automata Network Markup Language) to let users construct Automata machines programmatically or almost in the sense of a full custom design Micron supports via a visual workbench. “You can think of it like circuit design for the big data analytics machines that users want to deploy in the fabric,” he said.

Outside of the technology itself, one should note that Micron is leveraging an existing process and facility to manufacture this processor. In other words, despite the long R&D cycle behind it, the overhead for production looks to be relatively minimal.

Automata processing is a fringe concept, but one that was obscure enough for Micron to take to market in the name. “A lot of people aren’t familiar with automata,” said Dlugosch. “We thought about this a great deal before we decided to call this an automata processor—even though automata are implemented as conventional algorithms in a variety of ways in a variety of applications. They’re not always recognized as automata, but in the areas and end use cases we’re targeting they are and will be used and the concept of automata computing will become more common starting in the HPC space first.”

Even if many aren’t immediately familiar with automata, it’s Micron’s hope that its processor will drive recognition of this processor type into the mainstream—and hopefully directly into the laps of big government, life sciences and other companies in need of high performance large-scale data processing.

Subscribe to HPCwire's Weekly Update!

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

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Nvidia P100 Shows 1.3-2.3x Speedup Over K80 GPU on Financial Apps

April 20, 2017

When it comes to the true performance of the latest silicon, every end user knows that the best processor is the one that works best for their application. Read more…

By Tiffany Trader

Quantum Adds Global Smarts to StorNext File System

April 20, 2017

Companies that use Quantum’s StorNext platform to store massive amounts of data this week got a glimpse of new storage capabilities that should make it easier to access their data horde from anywhere in the world. Read more…

By Alex Woodie

HPE Extreme Performance Solutions

HPC-Driven Weather Simulations Improving Forecasting Capabilities

In September of 1938, a massive hurricane traversed the Atlantic Ocean and made landfall in New England. Due to inadequate and incorrect forecasting, the storm struck farther north and with greater intensity than had been predicted, leaving residents and authorities with virtually no warning or time to properly prepare. Read more…

Scaling an HPC Career in Nepal Can Be a Steep Climb

April 20, 2017

Umesh Upadhyaya works as an IT Associate at the International Centre for Integrated Mountain Development (ICIMOD) in Nepal, which supports the country’s one and only HPC facility. He is directly involved in an initiative that focuses on climate change and atmosphere modeling Read more…

By Nages Sieslack

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Intel Open Sources All Lustre Work, Brent Gorda Exits

April 19, 2017

In a letter to the Lustre community posted on the Intel website, Vice President of Intel's Data Center Group Trish Damkroger writes that effective immediately the company will be contributing all Lustre development to the open source community. Damkroger also announced that Brent Gorda, General Manager, High Performance Data Division at Intel is leaving the company. Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Penguin Takes a Run at the Big Cloud Providers

April 12, 2017

HPC specialist Penguin Computing recently re-ran benchmarks from a study of its larger brethren and says the results show its ‘public cloud’ – Penguin on Demand (POD) – is among the leaders in cost and performance. Read more…

By John Russell

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

HPC and the Colocation Datacenter – a Bridge Too Far?

April 7, 2017

A more standardised HPC platform approach is making the running of HPC projects within increasing financial reach. Read more…

By Clive Longbottom, Quocirca

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This