I flew to Chicago today to support our partner Aster Data’s Big Data Insight summit. This Chicago event is a part of series of roadshows that Aster is doing for customers in cities in the US and Europe. Today’s event was held in the trendy Hotel Sax and featured talks from analysts as well as partners (SAS, Microstrategy and Dell).
Attending his first Aster roadshow was their brand new CEO, Quentin Gallivan. As the post-event happy hour was winding down I grabbed a few minutes with Quentin. Here is what he had to say:
Some of the topics Quentin covers:
What he did before Aster: CEO of BI SaaS provider Pivot link; CEO of Postini a SaaS email security company, and key exec at Verisign.
Why Quentin decided to join Aster.
How he heard about the opportunity.
What he see’s as Aster’s opportunity.
How the Dell partnership allows Aster to deliver a total solution.
A few weeks ago a group from NVIDIA was out visiting Dell. Their Tesla series of GPU cards are the primary cards that are used in our newly announced C410X expansion chassis. Filling up the C410X with NVIDIA cards and attaching it to a server can bring about ginormous increases in compute performance, helping to make HPC and scaled-out deployments wicked fast.
So how did NVIDIA get from rendering graphics for first person shooters to creating GPUs that accelerate modeling, simulation, imaging, signal processing, etc? Listen to the interview below with Geoff Ballew of NVIDIA’s Tesla unit and learn.
Some of the ground Geoff covers:
NVIDIA’s not just for gaming any more
A few years ago found that their graphic chips were getting a lot of raw math horsepower, so they added a few extra features into the chips and built a suite of software so that the graphic cards could be used for general computation.
How hard was it to convince HPC customers to take NVIDIA seriously in the compute arena?
A couple of days ago Bret Piatt, who handles Technical Alliances for OpenStack, came up to Austin to have further discussion with our team’s software engineers around OpenStack. If you’re not familiar with OpenStack, it is an open source cloud platform founded on contributed code from Rackspace and NASA’s Nebula cloud.
The project was kicked off a couple of months ago at an inaugural design summit held here in Austin. The summit drew over 25 companies from around the world, including Dell, to give input on the project and collectively map out the design for the project’s two main efforts, Cloud Compute and Object Storage.
Since the summit, and the project’s subsequent announcement the following week at the OSCON Cloud Summit, the community has been digging in. The first object storage code release will be available this month and the initial compute release, dubbed the “Austin” release, is slated for October 21. Additionally, the second OpenStack Design Summit has been set for November 9-12 in San Antonio, Texas, and is open to the public.
OpenStack visits Dell
During Bret’s visit to Dell he met with a bunch of folks including two of our software architects, Greg Althaus and Rob Hirschfeld. The three talked about how things were going with the project since the summit as well as specific ways in which Dell can contribute to the OpenStack project.
Below you can see where I crashed the three’s whiteboard session and made them tell me what they were doing. I then followed them, camera in hand, down to the lab where Greg and Rob showed Bret the system that we have targeted for running OpenStack.
Some of the topics (L -> R) Bret, Greg and Rob touch on:
Bret: Getting ready for the object storage release in September and compute in October. Looking to get the right hardware spec’d out so that people can start using the solution once its released.
Rob: Learning about how the project is coming together since the design summit. Interested in how the 3 code lines, storage, NASA compute and Rackspace compute, along with the input that was gathered at the Design summit and community input, are coming together.
Greg and Rob take Brett to the lab to show him the C6100 which could be a good candidate for open stack.
Next step, getting OpenStack in the lab and start playing with it.
iland is a provider of cloud computing infrastructure with high-availability data centers specifically designed for cloud computing in Boston, Washington D.C., Houston, Los Angeles, Dallas, and London. To stay competitive in the cloud infrastructure business, iland needs to gain as much value as possible from every watt of power and every square foot of data center floor space.
One day over lunch they were introduced to the PowerEdge C6105 and were impressed with the product’s density and power efficiency. One thing led to another and here is iland’s CTO Justin Giardina talking about why they are so interested int the PowerEdge C6105.
Some of the points Justin makes:
The primary reasons iland wanted to talk to Dell about the 6105 were density and power draw.
iland can stack 20 servers in one cabinet and since each 6105 has 4 servers in it by filling the cabinet with 6105s they can in affect get 80 servers (4X the compute power per cabinet).
The system only pulls 3 amps from both power supplies.
The last couple of Dell Data Center Solutions offerings I’ve talked about, Viking and MDC, have been from the custom side of the house. Both of these solutions are targeted specifically at a few select large customers.
The subject of today’s post however, the PowerEdge C6105 server, is available to anyone running a scaled out environment. It, alongside the recently available C410X expansion chassis, represent the latest additions to the PowerEdge C line that we launched back in March.
Efficiency is its middle name
Designed to maximize performance per watt per dollar, the C6105 is ideal for energy and budget constrained scale-out environments. Targets include: Scale-out Web 2.0, hosting, and HPC applications where core count and power efficiency are the priority.
Want a closer look? Click below and product manager Steve Croce will give you a quick overview.
Some of the points Steve touches on:
The 6105 is very dense: essentially four servers in a 2U chassis
The system leverages “shared infrastructure,” e.g two power supplies for all four servers, four 2U fans to cool it, etc., which results in weight and power savings and allows for an extremely dense system.
The 6105 features the Opteron 4000 series which are focused on power efficiency
It holds 12 3.5 inch disks. Each server gets 3 disks.
Over the last few years, we have been working with some of the world’s biggest hyperscale data center operators, folks who are deploying thousands, to tens of thousands of servers at a time. Within this select group, the theme that keeps coming up over and over is uber-efficiency.
The customers that we’ve been working with in areas like Web 2.0 and hosting require solutions that are not only extremely dense, but also dramatically drive down costs. When operating at the scale that these organizations do, ultra-efficiency is not a nice to have; it’s one of the most important tools the organization has to drive profitability.
It is with these customers and with their need for ultra-efficiency in mind that we designed the newest edition to our custom light-weight server line-up: Viking, designed to “pillage” inefficiency
Some of the points Ed touches on:
Viking can hold eight or 12 server nodes in a 3U chassis
Each node is a single socket server with up to 4 hard drives & 16GB of RAM along with two gigabit ethernet ports
It supports Intel’s Lynnfield or Clarkdale processors which means its 2-4 core’s per processor
The chassis also features an integrated switch and includes shared power and cooling infrastructure
The system is cold-aisle serviceable which means everything you need to get to is right in the front.
Light weight servers have been gathering steam recently. Targeted at focused markets like hosting and Web 2.0 they feature the old school architecture of placing one CPU per server and running one OS/application on that server. The new twist here is that they can pack up to 12 servers per one 3U enclosure.
Below, Dell Data Center Solutions chief architect Jimmy Pike takes us through a short whiteboard discussion on how Moore’s law has driven us to multi-core architectures and virtualization and how, in the case of very focused applications, that same law is bringing us back to the future.
Some of the points Jimmy makes:
Given Moore’s law its implausible to continue to drive higher and higher clock rates. This has given rise to multi core architecture.
Native demand of applications on servers hasn’t kept paced with Moore’s law. This has resulted in virtualizaton, allowing you in effect to run multiple servers on a single system.
This same law is also driving us in the opposite direction, to light weight servers which feature a simple one server/one OS architecture in a very energy efficient, cost effective manner targeted at focused applications.
Last week at VMworld, Dell held a Super session where we debuted a video walking through our Modular Data Center (MDC). The group that I belong to, Data Center Solutions (DCS), created the MDC as a custom solution addressing the specific needs of a few of our big strategic customers.
(As background, the DCS group has been acting as a custom tailor to the “internet superstars” for over three years and we address customers’ needs by focusing on innovation from the individual node all the way through the data center itself.)
Don’t box me in
In the video you’ll notice that gone is the forced shipping container form factor and in its place, as the name implies, is a more efficient modular design that lets you mix and match components like Legos.
Take a look below as Ty Schmitt, the lead architect for modular infrastructure, literally walks you through the concept and gives you his insight behind the design:
[Spoiler Alert!] Some of the points Ty touches on:
A Module takes up half the space of a traditional data center
Clip on modules let you add capacity as you grow
There are 6-12 racks per module or 2500 servers which you can access through a central hallway
The modules come pre-integrated, pre-configured and pre-tested
With a modular data center you get a single point for power, a single point for IT, and a single point for cooling as opposed to the 1000s of points you’d normally get
Last month we introduced the PowerEdge C410X expansion chassis which, when populated with GPGPUs and attached to a server, brings about ginormous increases in performance in a very cost effective manner.
A couple weeks after the system debuted NextIO, who creates and sells virtualized IO capabilities, was looking to qualify the machine in their lab located here in Austin. Wanting to add that personal touch, Franklin Flint and Corbin Moore from our OEM solutions group decided to pack the system in the back of Franklin’s truck and hand deliver it to Bob Shaw at NextIO.
What you have below is a no-expenses-spared documentary of their journey. Enjoy!
As I mentioned in my last entry, the week before last I headed out to the TDWI World Conference in San Diego. Besides talking about Dell’s new BI practice, I was there to represent our data analytics partners, Aster Data and Greenplum. Both vendors also had booths of their own and I was able to grab some time with Jeff Zeisler, director of pre-sales engineers at Aster Data, to get an overview of their architecture. Here’s what Jeff had to say:
Some of the ground Jeff covers:
Aster is a MPP (massively-parallel processing) data warehouse solution. It runs on a cluster of commodity hardware that execute SQL queries in parallel.
The 3 layers to the architecture:
Queen tier – central location users use to submit queries. It figures out how to split up the query and send it to the next tier.
Worker tier – where most of the servers are located, where data is stored (locally on the servers) and where all the heavy lifting for processing occurs. The map reduce framework is built into this tier and sits right next to the SQL execution engine.
Loader and exporter tier: a separate tier of machines that can be used to load new data into the system for bulk loading.
How it works: Query gets broken up across all the machines, they each execute some portion of the query and the result are brought back together at the Queen and returned to the user.
Posted by Barton George 
