Posts Tagged 'High Performance Computing'

December 11, 2015

Under the Infrastructure: Customers and customs make global HPC sales leader Jerry Gutierrez’s job enjoyable

Happy holidays! We can’t believe the year is already winding down. Under the Infrastructure has been so caught up in sharing our SLayer stories with you that the days have just flown by.

Speaking of flying, we’re excited to introduce you to one of our world voyagers, Jerry Gutierrez. He’s a global high performance computing (HPC) sales leader (say that one five times fast!) based in our Dallas headquarters—but you’d be hard-pressed to find him there these days. From South America to Asia, his busy schedule has him in meetings all over the map—and enjoying every minute of it.

Last month, Gutierrez celebrated his three-year mark with us. You ready to meet him?

SOFTLAYER: How would you explain your job to a layperson?

JERRY GUTIERREZ: I help sales teams globally identify and close HPC or accelerated computing-related sales opportunities. I also work with our product and marketing teams by way of customer feedback, marketing initiatives, and go-to market strategies around our HPC and accelerated computing products.

SL: Tell us about a day in the life of doing your job.

GUTIERREZ: I’ll give you an example. I was in Brazil this past week, in Sao Paulo and in Rio de Janeiro. I met with the sales teams there and gave them my insight into our GPU products from NVIDIA, along with some roadmap information. We then showed a really nice NVIDIA GRID demo for the customers and ran a small workshop around GPU-accelerated virtual desktop infrastructure (VDI) environment. We aim to run these sessions with a small audience of technical influencers and we keep them interactive and hands-on. We traveled to one of the customer’s offices and showed a live demo to a full house—running their software on a virtual GPU-enabled workstation that was running from SoftLayer’s Sao Paulo data center.

After that, we took a flight to Rio, where we had additional meetings with the internal sales group and a workshop-style presentation with customers. I have a technical background, so I talked to them about the technology, showed the demo, and answered questions. I think this strategy is very effective and much more powerful than just doing a PowerPoint presentation and showing slides with the bits and bytes of the products we offer.

Following that, I met with a large local university and a couple of startups to discuss our Catalyst program. Because I’ve been with SoftLayer for quite a while as a former senior sales engineer and now in my current role, I’m comfortable speaking to everyone from large enterprise C-level execs to the fast moving startup groups.

Wherever I go, I’m excited to talk about SoftLayer. I enjoy that part of the job.

SL: People always wonder, “How does that apply to me?” when you’re showing them something new. You demonstrate how the platform can work for them.

GUTIERREZ: Absolutely. We find it very powerful. Customers get engaged. They sit up in their chairs. They ask questions. That’s very powerful to me. We almost take the sales part right out of it and we’re talking on a technical level: what are your challenges, what have you done so far, what’s worked, what hasn’t worked? In Brazil, the goal was to show, on a technical level, the capabilities of SoftLayer with NVIDIA technology running applications that they use in-house but deployed in the SoftLayer cloud—all with the same experience that they’re used to, with the added benefits of better security and scalability.

SL: So your position isn’t as much exclusively sales as it is possibilities.

GUTIERREZ: Right. Part of what I do is business development around accelerated computing (including GPUs) because I have a technical background, and I’m very passionate about it. (I actually manage the relationship overall between SoftLayer and NVIDIA). It’s very exciting see what our customers have created using our platform, especially with GPU technology.

SL: Your position is very global. What have you learned in dealing with customers around the world?

GUTIERREZ: Understanding the different cultures and what it means to do business in different cultures was a huge plus for me. For instance, in Japan, it’s very formal during business hours. But afterwards, you go to happy hour and people loosen up a little bit. I had several calls with our Japan team before I visited, and I felt there were some awkward silences. I didn’t know what the pauses meant because I wasn’t seeing their faces. I was wondering if I said something wrong or off. When I went to visit, I got to know their personalities. They want to ingest what you just said, so there’s a pause before they answer you. You can’t get a feel for personalities or body language over the phone, and video chat isn’t the same.

SL: If someone was interested in doing what you’re doing, what advice would you have?

GUTIERREZ: First, I would advise them to get a mentor. At SoftLayer, it’s extremely helpful for us to both have a mentor (and I would say a plus would be an IBMer that’s been with the company a while) and be a mentor—it’s actually highly encouraged at IBM, because that relationship can provide so many insights and help us along our career paths. Secondly, do what you love. If you love to be in front of customers and enjoy working with people and talking about technology like I do, pursue it. In my role, you’d want to have a technical background and a sales background as well. That’s really the mix for this role, since it’s very customer-facing—you’re doing presentations, thinking on the fly, and you need to be able to answer technical questions. Lastly, I would encourage them to pick a product, process, etc., to be the lead on or to champion and work to drive it and improve it. I found it very refreshing when I came to SoftLayer that it was not only open to this but that the company encouraged it—even though it was well out of my original job description. IBM is the same. Score!

SL: What’s the best places you’ve traveled and why?

GUTIERREZ: Tokyo and Rio. Tokyo is a very unique city. Tokyo is very clean, people are thoughtful and friendly. I’m a technical person and they have all the coolest technology. That’s the geek side of me talking! The food is fantastic, too. Rio is a totally different experience: beautiful beaches, beautiful weather, beautiful sights. The music, the food, it’s just phenomenal. And of course, the people. The people are extremely friendly.

SL: Those are pretty good favorites, we’d say.

Oh, and hey, if you’ve got any room in your suitcase, we wouldn’t mind hitching a ride around the world with you.

-Fayza

August 21, 2012

High Performance Computing - GPU v. CPU

Sometimes, technical conversations can sound like people are just making up tech-sounding words and acronyms: "If you want HPC to handle Gigaflops of computational operations, you probably need to supplement your server's CPU and RAM with a GPU or two." It's like hearing a shady auto mechanic talk about replacing gaskets on double overhead flange valves or hearing Chris Farley (in Tommy Boy) explain that he was "just checking the specs on the endline for the rotary girder" ... You don't know exactly what they're talking about, but you're pretty sure they're lying.

When we talk about high performance computing (HPC), a natural tendency is to go straight into technical specifications and acronyms, but that makes the learning curve steeper for people who are trying to understand why a solution is better suited for certain types of workloads than technology they are already familiar with. With that in mind, I thought I'd share a quick explanation of graphics processing units (GPUs) in the context of central processing units (CPUs).

The first thing that usually confuses people about GPUs is the name: "Why do I need a graphics processing unit on a server? I don't need to render the visual textures from Crysis on my database server ... A GPU is not going to benefit me." It's true that you don't need cutting-edge graphics on your server, but a GPU's power isn't limited to "graphics" operations. The "graphics" part of the name reflects the original intention for kind of processing GPUs perform, but in the last ten years or so, developers and engineers have come to adapt the processing power for more general-purpose computing power.

GPUs were designed in a highly parallel structure that allows large blocks of data to be processed at one time — similar computations are being made on data at the same time (rather than in order). If you assigned the task of rendering a 3D environment to a CPU, it would slow to a crawl — it handles requests more linearly. Because GPUs are better at performing repetitive tasks on large blocks of data than CPUs, you start see the benefit of enlisting a GPU in a server environment.

The Folding@home project and bitcoin mining are two of the most visible distributed computing projects that GPUs are accelerating, and they're perfect examples of workloads made exponentially faster with the parallel processing power of graphics processing units. You don't need to be folding protein or completing a blockchain to get the performance benefits, though; if you are taxing your CPUs with repetitive compute tasks, a GPU could make your life a lot easier.

If that still doesn't make sense, I'll turn the floor over to the Mythbusters in a presentation for our friends at NVIDIA:

SoftLayer uses NVIDIA Tesla GPUs in our high performance computing servers, so developers can use "Compute Unified Device Architecture" (CUDA) to easily take advantage of their GPU's capabilities.

Hopefully, this quick rundown is helpful in demystifying the "technobabble" about GPUs and HPC ... As a quick test, see if this sentence makes more sense now than it did when you started this blog: "If you want HPC to handle Gigaflops of computational operations, you probably need to supplement your server's CPU and RAM with a GPU or two."

-Phil

April 17, 2012

High Performance Computing for Everyone

This guest blog was submitted by Sumit Gupta, senior director of NVIDIA's Tesla High Performance Computing business.

The demand for greater levels of computational performance remains insatiable in the high performance computing (HPC) and technical computing industries, as researchers, geophysicists, biochemists, and financial quants continue to seek out and solve the world's most challenging computational problems.

However, access to high-powered HPC systems has been a constant problem. Researchers must compete for supercomputing time at popular open labs like Oak Ridge National Labs in Tennessee. And, small and medium-size businesses, even large companies, cannot afford to constantly build out larger computing infrastructures for their engineers.

Imagine the new discoveries that could happen if every researcher had access to an HPC system. Imagine how dramatically the quality and durability of products would improve if every engineer could simulate product designs 20, 50 or 100 more times.

This is where NVIDIA and SoftLayer come in. Together, we are bringing accessible and affordable HPC computing to a much broader universe of researchers, engineers and software developers from around the world.

GPUs: Accelerating Research

High-performance NVIDIA Tesla GPUs (graphics processing units) are quickly becoming the go-to solution for HPC users because of their ability to accelerate all types of commercial and scientific applications.

From the Beijing to Silicon Valley — and just about everywhere in between — GPUs are enabling breakthroughs and discoveries in biology, chemistry, genomics, geophysics, data analytics, finance, and many other fields. They are also driving computationally intensive applications, like data mining and numerical analysis, to much higher levels of performance — as much as 100x faster.

The GPU's "secret sauce" is its unique ability to provide power-efficient HPC performance while working in conjunction with a system's CPU. With this "hybrid architecture" approach, each processor is free to do what it does best: GPUs accelerate the parallel research application work, while CPUs process the sequential work.

The result is an often dramatic increase in application performance.

SoftLayer: Affordable, On-demand HPC for the Masses

Now, we're coupling GPUs with easy, real-time access to computing resources that don't break the bank. SoftLayer has created exactly that with a new GPU-accelerated hosted HPC solution. The service uses the same technology that powers some of the world's fastest HPC systems, including dual-processor Intel E5-2600 (Sandy Bridge) based servers with one or two NVIDIA Tesla M2090 GPUs:

NVIDIA Tesla

SoftLayer also offers an on-demand, consumption-based billing model that allows users to access HPC resources when and how they need to. And, because SoftLayer is managing the systems, users can keep their own IT costs in check.

You can get more system details and pricing information here: SoftLayer HPC Servers

I'm thrilled that we are able to bring the value of hybrid HPC computing to larger numbers of users. And, I can't wait to see the amazing engineering and scientific advances they'll achieve.

-Sumit Gupta, NVIDIA - Tesla

Subscribe to high-performance-computing