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          What is Specialized Hardware and Why Open Source Will Drive Adoption
          ====================================================================
       
          25 Feb 2021 Written by: [17]Mark Coleman
       
          Over 35 years ago, Alan Kay gave a now famous [18]talk at a seminar
          called Creative Think, during which he even more famously remarked:
          “People who are really serious about software should make their own
          hardware.”
       
          History has confirmed Kay's thesis repeatedly, and today’s
          cloud-fueled landscape is proving again just how impactful
          non-homogenous hardware can be.
       
          In the digital infrastructure space, a new class of hardware is
          emerging that includes SmartNICs, FPGAs, DPUs, TPUs, and custom
          Arm-based CPUs — each designed to accelerate particular workloads or
          applications, and to do so more efficiently than generic solutions. As
          these innovations take center stage and more users begin to wrap
          hardware around their software (instead of the other way around), we
          are watching the slow end to an era of homogenous CPU dominance, the
          onset of a powerful tool for innovation, and an exciting rallying
          point for the open source community.
       
          The one-size-fits-all approach of conventional server CPUs and systems
          architecture is increasingly inefficient for many contemporary
          workloads, because they are designed to run general purpose business
          logic. For applications that need to run at any kind of scale, it is
          much more efficient to design a “custom cloud” for that application.
          [19]Moore’s law is slowing down as consumer demand for content (like
          Netflix) and smart devices (like connected cars) is heating up.
       
          Power Consumption
          -----------------
       
          Both financial and ecological sustainability have made power
          consumption an increasingly central topic. Specialized hardware —
          optimized for particular use cases — requires less power than generic
          CPUs. For example, although there’s a lot in the news about the power
          consumed by GPUs (let alone ASICs or FPGAs) for mining
          cryptocurrencies, that consumption pales in comparison to the energy
          it would take to [20]use generic CPUs for the same job.
       
          Even within the CPU market we’re seeing how optimization for
          performance and power consumption is a major driver for change. Arm
          CPUs typically perform favorably against x86 based architectures on
          power consumption mainly because they are more purpose built for
          specific use cases. This is one of the reasons why Arm has been so
          successful in the battery conscious mobile device market — but we’re
          now starting to see these energy savings (and performance gains) move
          into more powerful devices, from Apple’s recent Arm based M1
          announcements, all the way to datacenter scale deployments from AWS’
          Graviton 2 and the Altra lineup from [21]chip startup Ampere.
       
          Performance
          -----------
       
          While power consumption is often an important consideration, sometimes
          it’s pure performance that’s the main driver. As mentioned above, GPUs
          are more efficient than generic CPUs for certain workloads such as
          video gaming and machine learning. But their ability to perform
          massively parallelized computations means they’re now finding adoption
          in fields as diverse as bioinformatics, intrusion detection, and video
          transcoding.
       
          Application Specific Integrated Circuits (ASICs) are about as
          specialized as hardware gets. It’s a chip created to perform a
          specific set of tasks and nothing else. They are the peak of
          performance and you’ll find them in every appliance around you — but
          from a developer point of view they’re boring, because we can’t
          program them!
       
          Enter the Field Programmable Gate Array (FPGA). “Field Programmable”
          literally as in, “in the field” or after manufacture. FPGAs consist of
          thousands of Configurable Logic Blocks (CLBs) and other components
          that can be programmed to make it behave like a microprocessor, or as
          an encryption unit, graphics card, or anything else you want it to be.
          FPGAs represent a programmable as-close-to-ASIC-as-possible compromise
          that has seen adoption in fields as disparate as high frequency
          trading and automotive (and more recently, [22]led by Microsoft, in
          cloud computing). However, FPGAs can perform poorly on power
          consumption.
       
          Scalability
          -----------
       
          Increasingly, we’re seeing the demand for power conscious, highly
          performant hardware at scale. This runs two ways, from the
          exponentially increasing scale of data being collected and processed
          each day, to the smaller scale of the kind of [23]edge data centers
          that we operate at Equinix. Specialized hardware is being used to help
          with both.
       
          As edge computing steps up to the demand of increasingly distributed
          data sources, the constrained nature of edge deployments requires that
          they’re architected with efficiency of every kind in mind. Companies
          betting on edge don’t have the luxury of running thousands of servers
          in a traditional data center, so the machines they do run will benefit
          heavily from specializing the hardware to the workload.
       
          Key to Success: Bottoms Up Adoption via Open Source
          ---------------------------------------------------
       
          The more specialized the hardware is to the application, the better
          the potential power consumption, performance or scalability. But there
          are clear trade-offs that can hinder the wide-spread adoption of
          specialized hardware: namely accessibility and compatibility.
       
          Due to its massive adoption, almost everything works on an x86 CPU,
          which provides a powerful incentive not to experiment with and adopt
          specialized hardware types. Hardware manufacturers face two problems
          when addressing the issue of compatibility:
       
            1. Where to prioritize their compatibility efforts,
       
            2. How to get all the work done?
       
          Open Source communities can help with both.
       
          In August, I wrote on the [24]WorksOnArm blog about the incredible
          energy that has been unleashed over the last four years by the cloud
          native computing movement. By attracting the attention of open source
          developers (who are naturally drawn to exciting new problem domains),
          Kubernetes and its family of cloud native projects revolutionized
          computing in 4 short years.
       
          Hardware manufacturers would be well advised to follow Arm’s lead.
          [25]From my previous article: the WorksOnArm project is a big reason
          why “when Ampere’s Altra systems land in data centers, all major CNCF
          projects will already be compatible.”Harnessing open source
          communities is no free lunch, however, as they need to be encouraged
          and enabled to succeed. Get it right though, and your new hardware
          startup might be able to offset significant development costs and
          build a community of eager adopters in one go. That is, of course, if
          you can also solve the accessibility problem.
       
          While it might seem obvious to say that in order for developers to
          innovate with specialized hardware, they will need access to it — it’s
          actually a little more complicated. An entire generation of developers
          have grown up with the cloud, which means that for the most part they
          expect to consume their hardware innovations through an API.
       
          This means that hardware manufacturers and everyone in the supply
          chain — from chip designers, system designers, datacenter architects,
          et al — are faced with a chicken and egg problem. They need cloud
          providers to adopt their hardware to get it into the hands of eager
          open source developers, but they need adoption to convince the cloud
          providers to stock their innovative new technology.
       
          Whether it be driven by the need to lower power consumption, increase
          performance or scalability, this exciting new wave of innovation in
          specialized hardware will be led by those who, as a key competency,
          activate and build their developer communities best.
       
          Mark ColemanAuthor
       
          Mark Coleman
       
          With a strong background in software and an entreprenurial spirit,
          Mark pairs his marketing acumen with his experience as a developer to
          grow and amplify the Developer Relations team at Equinix Metal.
       
          [17]Read more posts by Mark
       
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