NVIDIA Launches Fifth-Generation CUDA

By Michael Feldman

October 15, 2012

Chipmaker NVIDIA has released CUDA 5, its latest and greatest toolkit for GPU computing. This new version adds Kepler hardware support for the supercomputing crowd as well as extra functionality to boost developer productivity. CUDA 5 is being launched just a few months ahead of the new K20 GPU, which is scheduled to be available before the end of the year.

Supporting advanced hardware features and increasing developing friendliness have always been a priority for the CUDA software engineers, but with Intel’s Xeon Phi and its built-in support in Parallel Studio expected to be released about the same time as the K20, there is an additional incentive for NVIDIA to make its programming platform more CPU-like.

The CUDA 5 release candidate has been out since spring, so GPU computing enthusiasts already have a taste of what it can do. Will Ramey, senior product manager of the NVIDIA’s GPU Computing Software group, says from the level of interest he’s seen from the early release, he’s expecting it to have a significant impact. “I believe this is going to be our most successful and widely used CUDA release ever,” he told HPCwire.

As far as the Kepler hardware goes, CUDA 5 will support the new “dynamic parallelism” and RDMA-enabled GPUDirect – two significant additions that the new Kepler chips will bring to high performance computing. For most programmers, the first feature will have a more far-reaching impact on application development. Dynamic parallelism allows the GPU to spawn its own threads, rather than having to rely on the CPU host to do it. That means a whole host of codes that used to require too much CPU-GPU interaction to make for a feasible port, can now be transitioned to the Kepler GPUs without the constraint of the communication overhead.

To make that type of code development more comfortable, NVIDIA has come up with GPU callable libraries, whose routines can be called natively from the application code running on the graphics processor. Prior to this, all the standard libraries were callable from the host side only, which made sense since prior to dynamic parallelism, the CPU was in charge of the application’s control flow. The design allows for plug-in APIs and callbacks, which enables developers to extend the capabilities of these routines even further.

NVIDIA is getting the ball rolling here by providing its own CUDA BLAS (Basic Linear Algebra Subroutines) package as a callable library. But the more significant impact is that it will allow ISVs and third-party developers to create these libraries as well, and build up a set of kernel packages, which can be shared more widely across the GPU computing ecosystem

Further, these callable libraries can be compiled separately, just as you would in a typical CPU build environment (Prior to this, all the code for a GPU app had to compiled together as monolithic source deck.) So you can build a GPU kernel from a number of source files and just link the individual objects at build time. This particular feature has no dependency on the Kepler GPUs and dynamic parallelism, so it’s applicable to the Fermi generation GPUs as well.

Because you can compile each source file individually, developers can enjoy significantly faster turnaround during intensive software development. According to Ramey, one NVIDIA customer had an application that encapsulated around 47,000 lines of code, and if just a single line was changed, it took around a minute to recompile all the sources. With this capability, the customer’s library recompilation now takes about four seconds.

The GPUDirect feature, which includes a hardware assist for RDMA, is also supported in the CUDA 5 software. It allows code that runs in the GPU to exchange data with other GPUs or any PCIe devices, without needing to coordinate it through the CPU host (although GPUDirect-aware software is also required for the PCIe device). That saves time for both the CPU and GPU.

With GPUDirect, InfiniBand host adapters and PCIe-connected sensors can take advantage of the RDMA acceleration  by talking directly with the GPU. GE already has some of this technology working with some of its embedded systems outfitted with custom sensors that stream data into the graphics chip.

The final big addition in CUDA 5 is support for Linux and Mac OS development via an integration of NVIDIA’s Nsight development environment for Linux with the open source Eclipse IDE. CUDA 4 offered a shrink-wrapped development environment for Windows via a Visual Studio integration, but Linux users were left to cobble something together themselves. With CUDA 5, compiling, debugging, performance analysis, and other dev tools are now integrated into the Eclipse interface, providing a much more user-friendly interface for Linux developers.

As with the CUDA toolkits that went before it, this fifth generation is backward compatible all the way to the first G80 CUDA chip, when NVIDIA started its GPU computing push in earnest. As such, this latest version can target over 450 million GPUs in the field today. And since CUDA is free for the taking from NVIDIA’s developer site, there’s not much of a downside to pulling in this latest upgrade.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

ExxonMobil, NCSA, Cray Scale Reservoir Simulation to 700,000+ Processors

February 17, 2017

In a scaling breakthrough for oil and gas discovery, ExxonMobil geoscientists report they have harnessed the power of 717,000 processors – the equivalent of 22,000 32-processor computers – to run complex oil and gas reservoir simulation models. Read more…

By Doug Black

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

O&G Companies Create Value with High Performance Remote Visualization

Today’s oil and gas (O&G) companies are striving to process datasets that have become not only tremendously large, but extremely complex. And the larger that data becomes, the harder it is to move and analyze it – particularly with a workforce that could be distributed between drilling sites, offshore rigs, and remote offices. Read more…

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Weekly Twitter Roundup (Feb. 16, 2017)

February 16, 2017

Here at HPCwire, we aim to keep the HPC community apprised of the most relevant and interesting news items that get tweeted throughout the week. Read more…

By Thomas Ayres

Alexander Named Dep. Dir. of Brookhaven Computational Initiative

February 15, 2017

Francis Alexander, a physicist with extensive management and leadership experience in computational science research, has been named Deputy Director of the Computational Science Initiative at the U.S. Read more…

Here’s What a Neural Net Looks Like On the Inside

February 15, 2017

Ever wonder what the inside of a machine learning model looks like? Today Graphcore released fascinating images that show how the computational graph concept maps to a new graph processor and graph programming framework it’s creating. Read more…

By Alex Woodie

IDC: Will the Real Exascale Race Please Stand Up?

February 21, 2017

So the exascale race is on. And lots of organizations are in the pack. Government announcements from the US, China, India, Japan, and the EU indicate that they are working hard to make it happen – some sooner, some later. Read more…

By Bob Sorensen, IDC

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Drug Developers Use Google Cloud HPC in the Fight Against ALS

February 16, 2017

Within the haystack of a lethal disease such as ALS (amyotrophic lateral sclerosis / Lou Gehrig’s Disease) there exists, somewhere, the needle that will pierce this therapy-resistant affliction. Read more…

By Doug Black

Azure Edges AWS in Linpack Benchmark Study

February 15, 2017

The “when will clouds be ready for HPC” question has ebbed and flowed for years. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

Cray Posts Best-Ever Quarter, Visibility Still Limited

February 10, 2017

On its Wednesday earnings call, Cray announced the largest revenue quarter in the company’s history and the second-highest revenue year. Read more…

By Tiffany Trader

HPC Cloud Startup Launches ‘App Store’ for HPC Workflows

February 9, 2017

“Civilization advances by extending the number of important operations which we can perform without thinking about them,” Read more…

By Tiffany Trader

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

US, China Vie for Supercomputing Supremacy

November 14, 2016

The 48th edition of the TOP500 list is fresh off the presses and while there is no new number one system, as previously teased by China, there are a number of notable entrants from the US and around the world and significant trends to report on. Read more…

By Tiffany Trader

Lighting up Aurora: Behind the Scenes at the Creation of the DOE’s Upcoming 200 Petaflops Supercomputer

December 1, 2016

In April 2015, U.S. Department of Energy Undersecretary Franklin Orr announced that Intel would be the prime contractor for Aurora: Read more…

By Jan Rowell

D-Wave SC16 Update: What’s Bo Ewald Saying These Days

November 18, 2016

Tucked in a back section of the SC16 exhibit hall, quantum computing pioneer D-Wave has been talking up its new 2000-qubit processor announced in September. Forget for a moment the criticism sometimes aimed at D-Wave. This small Canadian company has sold several machines including, for example, ones to Lockheed and NASA, and has worked with Google on mapping machine learning problems to quantum computing. In July Los Alamos National Laboratory took possession of a 1000-quibit D-Wave 2X system that LANL ordered a year ago around the time of SC15. Read more…

By John Russell

Enlisting Deep Learning in the War on Cancer

December 7, 2016

Sometime in Q2 2017 the first ‘results’ of the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) will become publicly available according to Rick Stevens. He leads one of three JDACS4C pilot projects pressing deep learning (DL) into service in the War on Cancer. Read more…

By John Russell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

CPU Benchmarking: Haswell Versus POWER8

June 2, 2015

With OpenPOWER activity ramping up and IBM’s prominent role in the upcoming DOE machines Summit and Sierra, it’s a good time to look at how the IBM POWER CPU stacks up against the x86 Xeon Haswell CPU from Intel. Read more…

By Tiffany Trader

Leading Solution Providers

Nvidia Sees Bright Future for AI Supercomputing

November 23, 2016

Graphics chipmaker Nvidia made a strong showing at SC16 in Salt Lake City last week. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

Dell Knights Landing Machine Sets New STAC Records

November 2, 2016

The Securities Technology Analysis Center, commonly known as STAC, has released a new report characterizing the performance of the Knight Landing-based Dell PowerEdge C6320p server on the STAC-A2 benchmarking suite, widely used by the financial services industry to test and evaluate computing platforms. The Dell machine has set new records for both the baseline Greeks benchmark and the large Greeks benchmark. Read more…

By Tiffany Trader

What Knights Landing Is Not

June 18, 2016

As we get ready to launch the newest member of the Intel Xeon Phi family, code named Knights Landing, it is natural that there be some questions and potentially some confusion. Read more…

By James Reinders, Intel

KNUPATH Hermosa-based Commercial Boards Expected in Q1 2017

December 15, 2016

Last June tech start-up KnuEdge emerged from stealth mode to begin spreading the word about its new processor and fabric technology that’s been roughly a decade in the making. Read more…

By John Russell

Intel and Trump Announce $7B for Fab 42 Targeting 7nm

February 8, 2017

In what may be an attempt by President Trump to reset his turbulent relationship with the high tech industry, he and Intel CEO Brian Krzanich today announced plans to invest more than $7 billion to complete Fab 42. Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This