OEM Solutions

How Memory Driven Computing Is Going To Benefit OEM Industry

Around the world, the volume of available data is growing faster than our ability to process it and create insight. For years, we have relied on the ability to throw more and more general-purpose microprocessors at a problem to help with growing data processing needs. But as the data continues to multiply and become more complex, splitting problems between these cookie-cutter processors, each of which has a small amount of its memory, is fast becoming a dated and less efficient solution.

To unlock the insights and intelligence that live within ever-growing volumes of data, an entirely new computing architecture is needed. HPE demonstrates Memory Driven Computing, a concept that puts memory, not processing, at the center of the computing platform to realize performance and efficiency gain not possible today. The team behind HPE’s Machine research project is designing the first Memory-Driven Computing architecture, an entirely new computing architecture designed around memory rather than processors, where memory is central to the system, not just something tethered to a processor.

Such a system can hold hundreds of terabytes or even petabytes in memory at one time and can solve problems thousands of times faster than a conventional computer. From healthcare to transportation and retail, Memory-Driven Computing will unleash new opportunities for problem-solving and innovation. The goal is to eliminate inefficiencies in how memory, storage, and processors interact today to solve problems faster. HPE says it will reduce the time it takes to process complex calculations "from days to hours, hours to minutes," and will ultimately deliver real-time intelligence.  



Over the past decade, health data has gone digital with MRI images, genomic data, clinical trials, patient histories, and electronic health records of all sorts now reside in computing systems. It’s made possible by a confluence of technology trends that doctors, hospitals, and researchers capture more health data every year; computers have become more powerful, allowing them to keep up with growing data volumes; advances in analytics technology let medical professionals sift through all that data to identify patterns.

The problem to handle all that data is memory. Computers, even the most sophisticated ones, don’t have enough of it to perform these calculations efficiently. To devise personalized diagnoses and treatments, doctors and researchers need access to a patient’s entire medical history, as well as family health history, lifestyle data, and environmental exposures. Analysing all that in the context of billions of other medical profiles would identify matches of people, diagnoses and treatments or therapies that worked best for people most similar to the patient as opposed to treatments that work best for the average patient.

HPE’s exploring those implications through its first collaboration using Memory-Driven Computing architecture with the German Centre for Neurodegenerative Diseases (DZNE). Memory Driven Computing is contributing to the cure for Alzheimer’s disease. DZNE ran one component of gene assembly pipeline on a supercomputer with a traditional computing architecture in April, took 22 minutes to run the data. The last time they used The Machine – HPE’s Memory-Driven Computing system in early July, it took 36 seconds.



Let’s talk about another real issue these days. About 20 percent of all commercial airline flights are delayed, which usually has a domino effect throughout the air transport network, wreaking general havoc with reservations, baggage handling, gate changes, crew assignments and security. Transportation systems have so many variables that conventional computing systems aren’t able to evaluate them at once.  As a result, one system handles reservations. Another manages baggage handling. A third system processes gate and crew assignments.

Smart airports and transportation systems of the future will be equipped to solve, if not eliminate, these complex problems. With a huge pool of nonvolatile memory available, transportation companies and government agencies will be able to run what-if scenarios to identify the optimal response to common disruptions. Memory-Driven Computing can allow transportation systems to predict problems faster and with bigger datasets. For instance, an airport could simulate an almost infinite number of potential delays at different places around the terminal and hold the solution in memory so that it would know exactly how to respond the instant one of those delays occurred.



Imagine a future in which your favorite retailers anticipate your shopping needs, tastes and budget more accurately than your best friend can. Retailers are set to invest billions by 2020 on beacons, sensors and radio-identification tags. But all this data is useless unless companies can identify trends and customer needs before they expire, without trespassing on customers’ privacy or making them feel spied upon. The architecture of current computing systems makes retailers incapable of crunching enormous data sets without long lag times. But systems built on HPE’s Memory-Driven Computing architecture could deliver enormous gains in analytic capacity and provide actionable insights within the attention span of a shopper. Imagine looking at the entire purchase history of a customer compared to the shopping trends of 100 customers most similar to them—all while the customers are still in the aisles.


The OEM Advantage –

HPE plans to bring new memory solutions to market and accelerate adoption in every enterprise. All of this brings a major opportunity for OEM software vendors as well. It will enable smaller businesses to act faster than big, established competitors. OEM’s agreement with HPE will help counter growing data challenges faced by various business. When you’re launching your business or app, you have no idea how many users or customers you’ll acquire, nor how fast you’ll acquire them. One has to be future-ready to support massive scale transaction in a brisk of seconds.

By 2020, 100 billions of connected devices will melt existing technology. This new design is a complete rethink of the computing model, which lets OEM’s face growing data challenges in education, healthcare, transportation, science, and business.

Memory-driven computing is the solution to move the OEM industry forward in a way that can enable advancements across all aspects of society. This new architecture will have huge implications on OEM industry of every computing category– from intelligent edge devices to supercomputers.

The sheer growth of data and the resulting strain on organizations and their IT departments today is astronomical. HPE OEM is constantly seeking out opportunities to innovate and evolve technology platforms to serve its partners as they manage the data deluge. The OEM program will help customers tackle the data challenges ahead of them, and allows to evolve HPE’s technology—and business—for a new audience.

It’s an exciting moment for the company, but customers won’t have to look too far into the future to see the impacts of this shift towards Memory-Driven Computing in today’s data center. In fact, HPE is rapidly commercializing such technologies, many of which are related to The Machine project, into new and existing products. HPE’s idea with memory-driven computing — change the focus from the processors themselves to the stored data OEMs are manipulating. It involves three aspects:

  1. Use “non-volatile” memory — a way to store data without actively using power.
  2. Wherever possible, use photonics rather than ordinary electronics. Photons move faster than electrons and cost less energy to get moving.
  3. Switch the fundamental architecture, so that input/output and individual processors access the memory as directly as possible.

Working with this prototype, HPE will be able to evaluate, test and verify the key functional aspects of this new computer architecture and future system designs, setting the industry blueprint for the future of technology. HPE is confident that Memory-Driven future is ahead and will advance the technologies that will not only take the data deluge head-on but will also enable possibilities we have yet to imagine.


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