Doug Fuller, VP of Software program Engineering at Cornelis Networks


As Vice President of Software program Engineering, Doug is chargeable for all facets of the Cornelis Networks’ software program stack, together with the Omni-Path Structure drivers, messaging software program, and embedded gadget management methods. Earlier than becoming a member of Cornelis Networks, Doug led software program engineering groups at Pink Hat in cloud storage and knowledge companies. Doug’s profession in HPC and cloud computing started at Ames Nationwide Laboratory’s Scalable Computing Laboratory. Following a number of roles in college analysis computing, Doug joined the US Division of Vitality’s Oak Ridge Nationwide Laboratory in 2009, the place he developed and built-in new applied sciences on the world-class Oak Ridge Management Computing Facility.

Cornelis Networks is a expertise chief delivering purpose-built high-performance materials for Excessive Efficiency Computing (HPC), Excessive Efficiency Knowledge Analytics (HPDA), and Synthetic Intelligence (AI) to main business, scientific, tutorial, and authorities organizations.

What initially attracted you to pc science?

I simply appeared to get pleasure from working with expertise. I loved working with the computer systems rising up; we had a modem at our faculty that permit me check out the Web and I discovered it fascinating. As a freshman in faculty, I met a USDOE computational scientist whereas volunteering for the Nationwide Science Bowl. He invited me to tour his HPC lab and I used to be hooked. I have been a supercomputer geek ever since.

You labored at Pink Hat from 2015 to 2019, what have been a number of the initiatives you labored on and your key takeaways from this expertise?

My most important undertaking at Pink Hat was Ceph distributed storage. I would beforehand targeted solely on HPC and this gave me a possibility to work on applied sciences that have been vital to cloud infrastructure. It rhymes. Most of the rules of scalability, manageability, and reliability are extraordinarily related regardless that they’re aimed toward fixing barely totally different issues. By way of expertise, my most vital takeaway was that cloud and HPC have rather a lot to be taught from each other. We’re more and more constructing totally different initiatives with the identical Lego set. It is actually helped me perceive how the enabling applied sciences, together with materials, can come to bear on HPC, cloud, and AI purposes alike. It is also the place I actually got here to know the worth of Open Supply and execute the Open Supply, upstream-first software program improvement philosophy that I introduced with me to Cornelis Networks. Personally, Pink Hat was the place I actually grew and matured as a pacesetter.

You’re at present the Vice President of Software program Engineering at Cornelis Networks, what are a few of your obligations and what does your common day appear like?

As Vice President of Software program Engineering, I’m chargeable for all facets of the Cornelis Networks’ software program stack, together with the Omni-Path Structure drivers, messaging software program, cloth administration, and embedded gadget management methods. Cornelis Networks is an thrilling place to be, particularly on this second and this market. Due to that, I am unsure I’ve an “common” day. Some days I am working with my staff to unravel the most recent expertise problem. Different days I am interacting with our {hardware} architects to verify our next-generation merchandise will ship for our prospects. I am usually within the subject assembly with our wonderful group of consumers and collaborators ensuring we perceive and anticipate their wants.

Cornelis Networks gives subsequent era networking for Excessive Efficiency Computing and AI purposes, may you share some particulars on the {hardware} that’s supplied?

Our {hardware} consists of a high-performance switched cloth sort community cloth answer. To that finish, we offer all the mandatory units to totally combine HPC, cloud, and AI materials. The Omni-Path Host-Material Interface (HFI) is a low-profile PCIe card for endpoint units. We additionally produce a 48-port 1U “top-of-rack” change. For bigger deployments, we make two fully-integrated “director-class” switches; one which packs 288 ports in 7U and an 1152-port, 20U gadget.

Are you able to talk about the software program that manages this infrastructure and the way it’s designed to lower latency?

First, our embedded administration platform supplies simple set up and configuration in addition to entry to all kinds of efficiency and configuration metrics produced by our change ASICs.

Our driver software program is developed as a part of the Linux kernel. In actual fact, we submit all our software program patches to the Linux kernel group immediately. That ensures that every one of our prospects get pleasure from most compatibility throughout Linux distributions and straightforward integration with different software program equivalent to Lustre. Whereas not within the latency path, having an in-tree driver dramatically reduces set up complexity.

The Omni-Path cloth supervisor (FM) configures and routes an Omni-Path cloth. By optimizing visitors routes and recovering shortly from faults, the FM supplies industry-leading efficiency and reliability on materials from tens to 1000’s of nodes.

Omni-Path Categorical (OPX) is our high-performance messaging software program, just lately launched in November 2022. It was particularly designed to scale back latency in comparison with our earlier messaging software program. We ran cycle-accurate simulations of our ship and obtain code paths with a view to reduce instruction rely and cache utilization. This produced dramatic outcomes: whenever you’re within the microsecond regime, each cycle counts!

We additionally built-in with the OpenFabrics Interfaces (OFI), an open commonplace produced by the OpenFabrics Alliance. OFI’s modular structure helps reduce latency by permitting higher-level software program, equivalent to MPI, to leverage cloth options with out extra perform calls.

The whole community can also be designed to extend scalability, may you share some particulars on the way it is ready to scale so effectively?

Scalability is on the core of Omni-Path’s design rules. On the lowest ranges, we use Cray link-layer expertise to appropriate hyperlink errors with no latency influence. This impacts materials in any respect scales however is especially vital for large-scale materials, which naturally expertise extra hyperlink errors. Our cloth supervisor is concentrated each on programming optimum routing tables and on doing so in a speedy method. This ensures that routing for even the most important materials could be accomplished in a minimal period of time.

Scalability can also be a vital element of OPX. Minimizing cache utilization improves scalability on particular person nodes with massive core counts. Minimizing latency additionally improves scalability by bettering time to completion for collective algorithms. Utilizing our host-fabric interface assets extra effectively permits every core to speak with extra distant friends. The strategic selection of libfabric permits us to leverage software program options like scalable endpoints utilizing commonplace interfaces.

May you share some particulars on how AI is included into a number of the workflow at Cornelis Networks?

We’re not fairly prepared to speak externally about our inner makes use of of and plans for AI. That mentioned, we do eat our personal pet food, so we get to benefit from the latency and scalability enhancements we have made to Omni-Path to help AI workloads. It makes us all of the extra excited to share these advantages with our prospects and companions. We’ve definitely noticed that, like in conventional HPC, scaling out infrastructure is the one path ahead, however the problem is that community efficiency is well stifled by Ethernet and different conventional networks.

What are some adjustments that you simply foresee within the {industry} with the arrival of generative AI?

First off, using generative AI will make folks extra productive – no expertise in historical past has made human beings out of date. Each expertise evolution and revolution we’ve had from the cotton gin to the automated loom to the phone, web and past have made sure jobs extra environment friendly, however we haven’t labored humanity out of existence.

By the appliance of generative AI, I imagine firms will technologically advance at a sooner fee as a result of these operating the corporate may have extra free time to concentrate on these developments. As an example, if generative AI supplies extra correct forecasting, reporting, planning, and so on. – firms can concentrate on innovation of their subject of experience

I particularly really feel that AI will make every of us a multidisciplinary skilled. For instance, as a scalable software program skilled, I perceive the connections between HPC, huge knowledge, cloud, and AI purposes that drive them towards options like Omni-Path. Outfitted with a generative AI assistant, I can delve deeper into the that means of the purposes utilized by our prospects. I’ve little doubt that this may assist us design much more efficient {hardware} and software program for the markets and prospects we serve.

I additionally foresee an total enchancment in software program high quality. AI can successfully perform as “one other set of eyes” to statically analyze code and develop insights into bugs and efficiency issues. This can be notably fascinating at massive scales the place efficiency points could be notably troublesome to identify and costly to breed.

Lastly, I hope and imagine that generative AI will assist our {industry} to coach and onboard extra software program professionals with out earlier expertise in AI and HPC. Our subject can appear formidable to many and it might probably take time to be taught to “assume in parallel.” Basically, identical to machines made it simpler to fabricate issues, generative AI will make it simpler to contemplate and motive about ideas.

Is there the rest that you simply wish to share about your work or Cornelis Networks basically?

I would prefer to encourage anybody with the curiosity to pursue a profession in computing, particularly in HPC and AI. On this subject, we’re geared up with essentially the most highly effective computing assets ever constructed and we convey them to bear towards humanity’s best challenges. It is an thrilling place to be, and I’ve loved it each step of the best way. Generative AI brings our subject to even newer heights because the demand for rising functionality will increase drastically. I can not wait to see the place we go subsequent.

Thanks for the nice interview, readers who want to be taught extra ought to go to Cornelis Networks.