Search Results for: “cuda”

GPU-based Brain Research Hits it Out of the Park

Search Results for: cuda

The robot’s task is to learn the timing needed to hit a flying ball, mimicking the sort of visual thinking humans use to quickly learn how to navigate through the real world.

Over at the Nvidia Blog, Brian Caulfield writes that researchers in Japan has used GPUs and the CUDA parallel programming model to create a 100,000 neuron simulation of the human cerebellum, one of the largest simulations of its kind in the world. And they’ve put their model to the test by applying this knowledge to teach a robot to learn to hit a ball.

Our physical actions change the environment, which changes the sensory input to human brain our sensation. The brain then processes this changed sensory information and determines what action to take. It is called the ‘sensorimotor loop,’” Igarashi explains. “The brain must continue to choose appropriate actions on the basis of gradually-changing sensory information.”

One of the biggest challenges in modeling neural brain function: simulation speed. Using a CPU alone it took 98 seconds of compute time to figure out how to respond to a stimulus lasting just one second. Using GPUs resulted in a 100x speedup, giving the GPU-based system the speed needed to handle real world tasks.

To show their system in action, the researchers demonstrated their robotic system learning – in real time – how to hit a small plastic ball thrown by a toy pitching machine with a round plastic racket. Yamazaki believes his work could result in robots within 5 years that rely on a silicon cerebellum that will allow them to “think” – that is, they would be able to assess their environment and organize movements autonomously.

Read the Full Story.

Read the entire post …

Posted in Computing Research, GPUs, HPC, HPC Hardware | Leave a comment

Video: Amazing DigiCortex Engine Maps the Brain with GPUs

Search Results for: cuda

In this video from the 2013 GPU Technology Conference, Ivan Dimkovic and Ana Balevic describe the ground-breaking DigiCortex Engine. Recently ported to CUDA, the application has seen huge speedups with GPU computing.

DigiCortexis my hobby project implementing large-scale simulation and visualization of biologically realistic cortical neurons, synaptic receptor kinetic, axonal action potential propagation delays as well as long-term and short-term synaptic plasticity. Current version of DigiCortex is heavily optimized for Intel CPUs (including Sandy Bridge AVX instruction set). The first CUDA-enabled version with GPU acceleration (CUDA optimizations done by Ana Balevic) is available as of v0.95

The simulation footage in this video is really gorgeous, so be sure to watch it in HD mode. Read the Full Story.

Read the entire post …

Posted in Computing Research, Events, GPUs, GTC - GPU Technology Conference, HPC, HPC Hardware, Video | Leave a comment

GTC 2013: ARM + GPU = GPU’riffic, says Barcelona SCC

Search Results for: cuda

In this special guest feature, Dan Olds from Gabriel Consulting writes that the Barcelona Supercomputer Center is making a big bet on ARM processing for HPC.

Over the last few years, we’ve seen a steadily growing buzz surrounding the use of ARM chips in PCs, servers, and supercomputers. Here at GTC 2013, that buzz is even more pronounced due to NVIDIA’s upcoming Project Denver, and advances in their GPU technology that result in even less dependency on having a fast and powerful (read: Xeon) processor feeding the GPU number-crunching beasts. Our pal Rik Myslewski penned a great article on GTC 2013 ARM chatter here.

While most everyone has been debating and speculating about what it would be like to combine ARM processors and GPU accelerators, one organization has put together some hardware in order to separate the theoretical from the real. The Barcelona Supercomputer Center (from the Barcelona in Spain, not the other one) is building clusters to explore the potential advantages that might arise from combining low power ARM processors with fast number-crunching GPUs.

Their first attempt, the Tibadabo, was a proof of concept to determine whether it’s possible to build an all-ARM-based cluster. Could they really put together a cluster based on cell phone processors? And, if they could build it, could they find or adapt enough software for it to do useful work?

They were able to construct a two-rack cluster containing 32 blades, 256 nodes, and a total of 512 Tegra 2 ARM cores. They were able to port 11 scientific apps over to ARM with little difficulty, although they did need to fiddle around with the memory hierarchy to optimize some of the apps.

The performance wasn’t all that great. The total system turned out 512 GFLOPs while consuming 3.4 KW, yielding .015 GGLOPs/watt. For context, the best systems on the most recent Green500 list come in around 2.4 or 2.5 GFLOPs/watt, while the systems at the end of the list are rated at .033 GFLOPs/watt.

So they went back to the drawing board and, using NVIDIA’s CARMA development box, clustered 16 of them together as a learning experience they called Pedraforca v1. This system did much better than the ARM-only Tibadabo on energy efficiency, yielding .78 GFLOPs/watts on DGEMM and 5.04 in SGEMM (matrix multiply double and single precision), so they were making progress.

Limitations in the platform (PCIe max of 400 MB/s plus inability to overlap computation and data transfers) meant it couldn’t be scaled up very well. However, it did lead them to a new breakthrough in their thinking for their next system, which they’ve dubbed Pedraforca V2.

They’ve decided the key to building a highly efficient system isn’t to build an accelerated cluster but to build a cluster of accelerators. While there isn’t much difference in the words, there’s a world of difference between the meanings. With Pedraforca v2, they will be de-coupling the CPUs from the GPUs, meaning that the ratio of CPU-GPU can be changed to fit the workloads. They will also be using direct GPU-GPU data transfers via Mellanox’s ConnectX-3 Infiniband interconnects.

This will take a huge amount of latency out of the system and, accordingly, reduce the amount of work the CPU needs to do to orchestrate GPU communications. The prototype system will have 64 nodes which will utilize a quad-core Tegra 3 CPU that will slide into a 4x PCIe slot on a Mini-ITX carrier. In this configuration, the CPU will only be managing boot and MPI communications, plus minimal traffic cop duty for the GPUs. The point is that you don’t need a hugely fast and powerful processor to fulfill these requirements.

However, Pedraforca v2 will have some processing power in the form of Kepler-based NVIDIA K20 GPUs that can deliver 1,170 GFLOP/s through a PCIe Gen3 slot. The GPUs will be able to communicate with each other at 40 Gb/s via the aforementioned Mellanox-fueled Infiniband interconnect.

Both presenters pointed out that this isn’t a general purpose HPC system – it is intended as a host for apps that are GPU-optimized. While they didn’t discuss any FLOPs/watt estimates or performance predictions, it’s safe to say that this system should be an eye opener when it comes to energy efficiency and even cost per FLOP. It’s definitely a project worth watching.

Read the entire post …

Posted in Compute, GPUs, Green HPC, HPC, HPC Hardware | Leave a comment

Rob Farber on the Far-reaching HPC Implications from GTC 2013

Search Results for: cuda

In this video, CUDA book author Rob Farber discusses the recent Nvidia keynote at the 2013 GPU Technology Conference. As a technologist, Rob thinks some of the things that weren’t said by Nvidia CEO Jen-Hsun Huang during the talk are very significant in terms of high performance computing and the business of accelerated computing.

Read the entire post …

Posted in Business of HPC, Events, GPUs, GTC - GPU Technology Conference, HPC, HPC Hardware, Video | 2 Comments

Video: A Closer Look at the Kayla ARM-based Development Platform for CUDA and OpenGL

Search Results for: cuda

In this video from the GPU Technology Conference, Ian Buck from Nvidia describes the new Kayla development platform for ARM-based CUDA and OpenGL.

“Introducing the Kayla Platform for computing on the ARM architecture – where supercomputing meets mobile computing. The Kayla platform is powered by an NVIDIA Tegra Quad-core ARM processor and a Kepler GPU to deliver the highest performance, highest efficiency for the next generation of CUDA and OpenGL application. Pre-installed with CUDA 5 and supporting OpenGL 4.3, it provides ARM applications development across the widest range of application types. The Kayla platform will be available Spring 2013.”

Read the Full Story.

Read the entire post …

Posted in Cuda, Events, GTC - GPU Technology Conference, HPC, HPC Software, Video | Leave a comment

Day 2 Keynote from GTC: Parallel Processing of the Genomes

Search Results for: cuda



Video streaming by Ustream

At insideHPC, we are very pleased to bring you live streaming keynotes from the GPU Technology Conference this week in San Jose.

In this video, Erez Lieberman Aiden from the Baylor College of Medicine presents a keynote talk entitled: Parallel Processing of the Genomes, by the Genomes and for the Genomes.

The human genome is a sequence of 3 billion chemical letters inscribed in a molecule called DNA. Famously, short stretches (~10 letters, or “base pairs”) of DNA fold into a double helix. But what about longer pieces? How does a 2 meter long macromolecule, the genome, fold up inside a 6 micrometer wide nucleus? And, once packed, how does the information contained in this ultra-dense structure remain accessible to the cell? This talk will discuss how the human genome folds in three dimensions, a folding enables the cell to access and process massive quantities of information in parallel. To probe how genomes fold, we developed Hi-C, together with collaborators at the Broad Institute and UMass Medical School. Hi-C couples proximity-dependent DNA ligation and massively parallel sequencing. To analyze our data and reconstruct the underlying folds, we, too must engage in massively parallel computation. I will describe how we use NVIDIA’s CUDA technology to analyze our results and simulate the physical processes of genome folding and unfolding.


Read the entire post …

Posted in Computing Research, Events, GTC - GPU Technology Conference, HPC | Leave a comment

Python for CUDA to Bolster Next Wave of GPU-powered HPC and Big Data Analytics

Search Results for: cuda

Today Nvidia announced that growing ranks of Python users can now take full advantage of GPU acceleration for HPC and Big Data analytics applications by using the CUDA parallel programming model. As a popular, easy-to-use language, Python enables users to write high-level software code that captures their algorithmic ideas without delving deep into programming details. Python’s extensive libraries and advanced features make it ideal for a broad range of HPC science, engineering and big data analytics applications.

Our research group typically prototypes and iterates new ideas and algorithms in Python and then rewrites the algorithm in C or C++ once the algorithm is proven effective,” said Vijay Pande, professor of Chemistry and of Structural Biology and Computer Science at Stanford University. “CUDA support in Python enables us to write performance code while maintaining the productivity offered by Python.”

Support for CUDA parallel programming comes from NumbaPro, a Python compiler in the new Anaconda Accelerate product from Continuum Analytics. This support was made possible by Nvidia’s contribution of the CUDA compiler source code into the core and parallel thread execution backend of LLVM, a widely used open source compiler infrastructure. Read the Full Story.

Read the entire post …

Posted in Cuda, Events, GTC - GPU Technology Conference, HPC Software, Python | Leave a comment

GTX TITAN: “The Ultimate CUDA Development GPU”

Search Results for: cuda

Over at the Nvidia Blog, Roy Kim writes that the new Kepler-based GTX TITAN is the ultimate CUDA development GPU.

1.3 Teraflops for Under $1,000

For the first time, GTX TITAN provides access to developers to over a teraflop of double-precision performance in a commercially-available GPU, transforming their PCs into personal supercomputers. That’s big news: for scientists, accessibility to computing resources is one of the biggest hurdles in advancing research. Many have to wait weeks to months for access to a supercomputer or a campus-wide cluster.

Read the Full Story.


Read the entire post …

Posted in Cuda, GPUs, HPC, HPC Hardware, HPC Software | Leave a comment

Interview: Nvidia’s Andy Walsh Previews Next Week’s GPU Technology Conference

Search Results for: cuda

 
The GPU Technology Conference kicks off next week in San Jose with a focus on scientific computing. The conference has grown considerably over the years, so I caught up with NVIDIA’s Andy Walsh to learn more. Walsh currently serves as Director of Marketing for their Accelerated Computing Business.

insideHPC: What will be new and exciting this year for the HPC crowd at GTC?

Andy Walsh: We’ve come a long way since the first GTC. In 2009, we created GTC to engage a diverse group of developers, scientists, and researcher using CUDA GPUs. The response then was much greater than we could imagine.

GTC has become the most important event showcasing breakthroughs in science and industry, thousands of the brightest minds will gather at GTC to meet, network and share ideas. This year’s conference will feature 400+ sessions and attendees from over 40 countries. What’s new this year is we expanded the scope to include tracks in manufacturing and design, media and entertainment, cloud computing, game and mobile development, and more. Attendees also will experience interesting things up and down the concourse from test driving state of the art cars to over 150 research posters.

insideHPC: How big are the exhibits this year?

Andy Walsh: GTC 2013 is expected to have our best exhibit area ever, with the largest numbers of companies exhibiting. This year, over 100 of the most important companies in the industry will be showcasing cutting edge offerings from HPC to mobile technology. We are also featuring companies that have joined us for the very first time, including Cisco, Citrix, VMware, IGI, Microsoft, Ingram Micro, Quantel, and Acer. Lunches and cocktail receptions are held in the exhibit hall, making the GTC exhibits area a vibrant place to network and learn about GPU solutions.

insideHPC: I’m particularly excited about the Emerging Companies Summit. Can you tell us more about that?

Andy Walsh: The Emerging Companies Summit (ECS) provides an opportunity for startups to showcase how they are using GPUs to transform industries and create new ones. This year, ECS will feature 16 companies from around the world advancing diverse fields, as well as a “CEO on Stage” event – where executives will present their companies to a panel of investors, analysts and tech leaders who will challenge the presenters with questions and provide insightful feedback. Five top startups will be recognized for their innovation in a competition with more than $75,000 in prizes.

insideHPC: When does it all begin next week?

Andy Walsh: GTC 2013 starts on Monday, March 18, with a full-day of preconference tutorials on a variety of topics including GPU programming languages and libraries to application optimization, visualization, video processing, and ray tracing.

On Tuesday, March 19, NVIDIA CEO and Co-Founder Jen-Hsun Huang will officially kick off a week of GTC sessions with the delivery of the opening keynote.

To see the full schedule of over 400 sessions, visit the GTC sessions and schedule page.

Read the entire post …

Posted in Events, GPUs, GTC - GPU Technology Conference, HPC, HPC Hardware | Leave a comment

Michael Wolfe on PGI’s All-new, Gnu-compatible C++ Compiler

Search Results for: cuda

In this video, Michael Wolfe from The Portland Group describes PGI’s new release with support for C++. Their all-new gnu-compatible C++ compiler includes the full suite of PGI optimizations plus support for CUDA-x86, OpenMP and OpenACC. The new EDG 4.5 front-end also supports many C++11 language features.

Wolfe also hints at a ground-breaking PGI demo planned for the GPU Technology Conference in March 2013.

Read the entire post …

Posted in Events, GTC - GPU Technology Conference, HPC, HPC Software, Video | Leave a comment

HPC Advisory Council Workshop Returns to Lugano March 13-15

Search Results for: cuda

The HPC Advisory Council Switzerland Conference returns to Lugano March 13-15, 2013.

The conference will focus on the following topics: Progress of Exascale in the European Union, high-performance interconnects, Accelerators and Parallel I/O, communication libraries (MPI, SHMEM, PGAS), GPU computing (CUDA, OpenCL) Big Data, advanced topics / technologies / development including server and storage systems, and hands-on clustering, network, troubleshooting, tuning, optimizations. The conference is open to the public and will bring together system managers, researchers, developers, computational scientists and industry affiliates.

Having been to this event several times, I can tell you that Lugano is one of the most beautiful towns in the world. It’s a solid three-day workshop, and this year they’ll be treating attendees to a boat trip on lake Lugano with an on-board apero and dinner.

Check out the Preliminary Agenda and Register now.

Read the entire post …

Posted in Events, HPC, HPC Advisory Council Workshop | Leave a comment

Crowdsourcing HPC: Kickstarter Project to Build GPU Nodes to Advance Science

Search Results for: cuda

In our second story on crowdsourced HPC this week, Dean Sheaffer describes the Computing for the Advancement of Science Kickstarter project, which aims to leverage Berkeley Open Infrastructure Network Computing (BOINC) platform.

Donors will help fund five (5) PC platforms designed to run just the BOINC client — 24/7/365. One of the nuances of the BOINC client is that it utilizes CUDA processing cores native to modern graphics cards. With four advanced graphic cards (each with 1,500+ CUDA cores) multiplied by the five PC Platforms, a total of 30,000 CUDA cores will be dedicated to advancing the scientific projects — All day, every day.

Read the Full Story.

Read the entire post …

Posted in Cloud HPC, HPC, inside Startups, Video | Leave a comment

Nvidia Adds New Cuda Education Centers, Beefs up Program Rewards

Search Results for: cuda

Over at the Nvidia Blog, Chandra Cheij writes that another 10 institutions from six countries were added this past quarter to our roster of CUDA Research Centers and CUDA Teaching Centers, bringing the total to 238. Now in 42 countries, CUDA Teaching Centers equip tens of thousands of students graduating each year with the knowledge and expertise to take advantage of the parallel processing power of GPUs. They get free teaching kits, textbooks, software licenses, NVIDIA CUDA architecture-enabled GPUs for teaching lab computers and academic discounts for additional hardware.

Separately, we are excited to announce that we’ve upgraded our Center Rewards Program. Anyone at one of our CUDA Centers can receive a 15 percent discount on all the latest Tesla Kepler GPU accelerators from any preferred solution provider. The CUDA Center Reward Pricing applies to Tesla K20X for servers, Tesla K20 for servers and workstations and Tesla K10 for servers (some limitations will apply).

Read the Full Story.

Read the entire post …

Posted in GPUs, HPC, HPC Education and Training, HPC Hardware | 1 Comment

The Portland Group Updates HPC Compilers and Development Tools

Search Results for: cuda

Today The Portland Group (PGI) announced new developer tools with expanded support for programming HPC accelerators along with industry-leading multi-core x64 performance. Now available for Linux, Apple OS X and Microsoft Windows, the 2013 release of the PGI high-performance parallelizing compilers and development tools are now available.

The high-performance computing landscape is evolving rapidly. With the recent introduction of new accelerators from NVIDIA, Intel and AMD, HPC users have more options than ever,” said Douglas Miles, director of The Portland Group. “With PGI 2013, we are expanding support within our PGI Accelerator programming tools so developers wishing to access the huge potential performance of these new platforms can do so in a consistent, productive and portable way.”

Highlights include:

  • The PGI) announced new developer tools with expanded support for programming HPC accelerators along with industry-leading multi-core x64 performance.”>PGI Accelerator native Fortran 2003 and C99 compilers expands support for the OpenACC directive-based accelerator programming model through the addition of an all-new PGI Accelerator C++ compiler. All three compilers feature expanded support for the OpenACC standard as well as new PGI extensions for supporting multiple devices. PGI Accelerator compilers also now target the latest NVIDIA Tesla K20 and K20X GPUs.
  • Support for targeting Intel Xeon Phi coprocessors and AMD APUs and discrete GPUs with OpenACC is planned for a future release.
  • New CUDA Fortran extensions in PGI 2013 include support for textures as well as support for dynamic parallelism and separate compilation on suitable CUDA-enabled hardware. Both PGI Accelerator and CUDA Fortran now support the latest CUDA 5.0 software environment from NVIDIA in addition to supporting multiple devices from a single program or host thread.

SPECompG_base2012 relative performance as measured by The Portland Group during the weeks of January 28 and February 4, 2013. The number of OpenMP threads was set to match the number of cores on each system.

In addition to expanded support for accelerators, PGI 2013 also delivers significantly faster performance on multi-core x64 processors including industry-leading OpenMP parallel performance on the new SPEC® OMP2012 benchmark suite running on the latest AVX-enabled processors from AMD and Intel. Overall performance on the SPEC CPU 2006 floating-point benchmarks is over 10% faster compared to the initial version of PGI 2012 released in February 2012. Similar performance gains have been seen on other HPC benchmarks as well.

Additional performance information is available at the PGI Benchmark page. Read the Full Story.

Read the entire post …

Posted in HPC | Leave a comment

Using GPUs to Improve Rotorcraft Safety

Search Results for: cuda

This week the CUDA Developer Zone features an interview with Monica Syal, an Aerospace Engineer at Advanced Rotorcraft Technology (ART). Syal is working on the development of a real-time rotorcraft brownout simulation facility for flight simulator applications. Brownout dust clouds develop because of rotor downwash flow, which impinges upon the ground and uplifts dust particles. The underlying physics is basically a dual-phase fluids problem, one fluid phase being the air and the other being the dust.

The simulation of the individual particle motions in the dust clouds is equivalent to an N-body problem, where the number of bodies (or particles) is very large, in this case of the order of 1014. We are using several techniques to expedite such simulations, some of these being smart algorithms (e.g., fast multipole methods), particle clustering algorithms, and high-performance parallel computing techniques. An obvious way to achieve the needed computational accelerations by using parallel computing is to conduct the simulations using as many computing resources as possible. The number of cores used in a CPU is relatively few and the CPUs are optimized for serial processing. On the other hand, a GPU consists of hundreds of cores, which can be used to parallelize the computationally intensive parts of the simulations. Therefore, we decided to use high-end Tesla GPUs to conduct these simulations. This has provided us with about two orders of magnitude speedup in the computational time compared to the serial execution of the code.

This research will help enhance flight safety and reduce the large number of brownout related accidents that occur in both military and civil rotorcraft flight operations. Read the Full Story.


Read the entire post …

Posted in GPUs, HPC, HPC Hardware, Visualization | Leave a comment

Advertisement

ClusterStor Ad

Video Archive

insideHPC.com is a production of insideHPC, LLC. © 2006-2013 Sitemap