|  CUDA, Supercomputing for the Masses: Part 7 Dr.Dobb’s Portal CUDA and CUDA-enabled devices are co-evolving to deliver more performance and capability with each new generation. NVIDIA's recent introduction of the GeForce 200-series and Tesla 10-series of products, shows the rapidity of this evolution as roughly twice the hardware capability is now available at the same price point of the previous line of products plus the 200-series includes the addition of some valuable (and potentially indispensable) new features. 08/20/2008 NVIDIA's GeForce GPUs Used for More Than Graphics HPCwire New consumer application pack uses NVIDIA CUDA technology to improve performance beyond graphics on NVIDIA GeForce GPUs. Consumers want blazing fast performance -- whether blasting their way through the latest game or being socially responsible and sharing their PC's processing power to help find cures for diseases. 08/12/2008 Larrabee, CUDA and the quest for the free lunch TG daily Opinion – Intel unveiled some key details about its upcoming Larrabee accelerator/discrete graphics architecture earlier this week, sparking speculation how this new technology will stack up to what is already out there in the market. 08/6/2008 NVIDIA Recognizes University Of Utah As A Cuda Center Of Excellence NVIDIA Corporation NVIDIA Corporation, the worldwide leader in visual computing technologies, and the University of Utah today announced that the university has been recognized as a CUDA Center of Excellence, a milestone that marks the beginning of a significant partnership between the two organizations. 07/31/2008 Processor Bifurcation Linux Magazine The processor market is diverging between two paths, the general and the predictable. Where does HPC hitch it’s wagon? 07/29/2008 CUDA, Supercomputing for the Masses: Part 6 Dr.Dobb’s Portal Astute readers of this series timed the two versions of the reverse array example discussed in Part 4 and Part 5 and were puzzled about how the shared memory version is faster than the global memory version. 7/25/2008 Parallel computing with GPUs InfoWorld Writing highly parallel code is hard, but many of us are going to need to learn to do it in the next few years, since computers are now getting more cores and bigger caches instead of faster clocks. Writing good parallel code for symmetric multi-processor computers with shared memory is hard enough, but when it becomes asymmetric, more than a little art is required. 07/25/2008 NVIDIA Accelerates the Search for a Cure HPCwire Stanford University's distributed computing program Folding@home has become a major force in researching cures to life-threatening diseases such as cancer, cystic fibrosis, and Parkinson's disease by combining the computing horsepower of millions of processors to simulate protein folding. 07/24/2008 NVIDIA Keeps It Interesting HPCwire NVIDIA is continuing to push hard on CUDA, the company's C-based software environment for GPU computing. With last month's announcement of the first CUDA Center of Excellence at the University of Illinois at Urbana-Champaign, NVIDIA said it donated half a million dollars to the school. 07/24/2008 Graphics Chips Help Supercomputers Become Commonplace ComputerWeekly.com The sight of supercomputers in every home and office may soon become a reality thanks to video games such as Grand Theft Auto. High-end 3D games need the fastest graphics chips to run well. This has driven graphics cards makers to build ever-faster cards, and performance from the graphics processor on these cards is hundreds of times faster than the processor in a standard PC. 07/07/2008 CUDA, Supercomputing for the Masses: Part 5 Dr.Dobb’s Portal The local and global memory spaces are not cached which means each memory access to global memory (or local memory) generates an explicit memory access. So what does it cost to access (read or write, for example) each of the different memory types? 06/30/2008 Tesla 10 & CUDA 2.0: Technical Analysis & Performance - Page 1 Beyond 3D CUDA was announced along with G80 in November 2006, released as a public beta in February 2007, and then finally hit the Version 1.0 milestone in June 2007 along with the launch of the G80-based Tesla solutions for the HPC market. Today, we look at the next stage in the CUDA/Tesla journey: GT200-based solutions, CUDA 2.0, and the overall state of NVIDIA's HPC business. 06/26/08 More Details on Elemental's GPU Accelerated H.264 Encoder AnandTech Elemental's software, if it truly performs the way as seen here, has the potential to be a disruptive force in both the GPU and CPU industries. On the GPU side it would give NVIDIA hardware a significant advantage over AMD's GPUs, and on the CPU side it would upset the balance between NVIDIA and Intel. Video encoding has historically been an area where Intel's CPUs have done very well, but if the fastest video encoder ends up being a NVIDIA GPU -- it could mean that video encoding performance would be microprocessor agnostic, you'd just need a good NVIDIA GPU. 06/24/08 Stanford releases beta Nvidia folding client The Tech Report “At last, Stanford University has released a beta version of the GPU2 Folding@home client for Nvidia graphics cards. You can grab the client from this post on the official FAH forums, although Stanford's Adam Beberg suggests users closely read the FAQ page to familiarize themselves with the software first.” 06/20/2008 NVIDIA, CUDA and PhysX EuroGamer “3D card manufacturers shouldn't take this the wrong way, but it takes a lot to make us crawl out of the communal Eurogamer bed (yes, all the Eurogamer writers share a single large bed - we do it for frugality and communality, which remain our watchwords) and go to a hardware presentation. There's a nagging fear someone may talk maths at us and we'd come home clutching the local equivalent of magic beans. And then we'll be laughed at by our fellow writers and made to sleep in the chilly end where the covers are thin and Tom left dubious stains. That's no fun at all.” 06/20/2008 NVIDIA's CUDA: The End of the CPU? Tom's Hardware CUDA is not a gimmick intended for researchers who want to cajole their university into buying them a GeForce. CUDA is genuinely usable by any programmer who knows C, provided he or she is ready to make a small investment of time and effort to adapt to this new programming paradigm. That effort won’t be wasted provided your algorithms lend themselves to parallelization. 06/18/2008 OptiTex to Use NVIDIA's CUDA Technology TenLinks.com "OptiTex' software is an ideal fit for NVIDIA as it leverages the combined personalities of our CUDA enabled GPUs - rich graphics and data intensive computation," said Andy Keane general manager of the GPU Computing business at NVIDIA. "OptiTex' software will deliver new levels of creative freedom for designers." 06/16/2008 NVIDIA Looking to Take Computing to the Next Level SFGate.com “NVIDIA released a new set of GPUs that not only boast a crazy amount of speed, but come with the promise of helping take on a larger set of tasks by delivering a lot more usable horsepower.” 06/16/2008 NVIDIA Releases 240-Core Graphics Processor eWeek.com “Tesla 10 series processor is Nvidia's latest offering for high-performance computing.” 06/16/2008 Nvidia and Stanford Finalizing Folding@Home Client for GeForce GPUs tgdaily “During Nvidia Editor's Day, we learned that Nvidia and the Folding@Home research group led by Vijay Pande are making final preparation to launch the first version of the Folding@Home client for Nvidia graphics processors.” 06/13/2008 Apple Eyeing NVIDIA's CUDA Technology? CNET “One of the most important performance challenges facing CUDA Apple's Worldwide Developers Conference is expected to cover the parallel tracks of Mac and iPhone software development, but the company may have another aspect of parallelism to discuss.” 06/06/2008 CUDA, Supercomputing for the Masses: Part 4 Dr.Dobb’s Portal “One of the most important performance challenges facing CUDA (short for "Compute Unified Device Architecture") developers is the best use of local multiprocessor memory resources such as shared memory, constant memory, and registers.” 06/03/2008 CUDA, Supercomputing for the Masses: Part 3 Dr.Dobb’s Portal “Congratulations! Thanks to Part 1 and Part 2 of this series on CUDA (short for "Compute Unified Device Architecture"), you are now a CUDA-enabled programmer with the ability to create and run programs that can use many hundreds of simultaneous threads on CUDA-enabled.” devices.” 05/13/08 Going to the Wall Advanced Imaging Magazine “Some jobs are just too big for one person, one company or one technology. In oil and gas exploration, for example, one seismic survey can equal 10 terabytes of data.” 05/15/08 CUDA and acceleration scalability.org “Took a Cuda class. Installed Cuda on my laptop. Well, 1.1 on my laptop. It has a Cuda class GPU (one of the things I made sure of when I bought it). 2.0 is in beta, and I think I will use that.” 05/13/08 Graphics Chips Help Supercomputers Become Commonplace ComputerWeekly.com The sight of supercomputers in every home and office may soon become a reality thanks to video games such as Grand Theft Auto. High-end 3D games need the fastest graphics chips to run well. This has driven graphics cards makers to build ever-faster cards, and performance from the graphics processor on these cards is hundreds of times faster than the processor in a standard PC. 07/07/2008 Tesla 10 & CUDA 2.0: Technical Analysis & Performance - Page 1 Beyond 3D CUDA was announced along with G80 in November 2006, released as a public beta in February 2007, and then finally hit the Version 1.0 milestone in June 2007 along with the launch of the G80-based Tesla solutions for the HPC market. Today, we look at the next stage in the CUDA/Tesla journey: GT200-based solutions, CUDA 2.0, and the overall state of NVIDIA's HPC business. 06/26/08 More Details on Elemental's GPU Accelerated H.264 Encoder AnandTech Elemental's software, if it truly performs the way as seen here, has the potential to be a disruptive force in both the GPU and CPU industries. On the GPU side it would give NVIDIA hardware a significant advantage over AMD's GPUs, and on the CPU side it would upset the balance between NVIDIA and Intel. Video encoding has historically been an area where Intel's CPUs have done very well, but if the fastest video encoder ends up being a NVIDIA GPU -- it could mean that video encoding performance would be microprocessor agnostic, you'd just need a good NVIDIA GPU. 06/24/08 Stanford releases beta Nvidia folding client The Tech Report “At last, Stanford University has released a beta version of the GPU2 Folding@home client for Nvidia graphics cards. You can grab the client from this post on the official FAH forums, although Stanford's Adam Beberg suggests users closely read the FAQ page to familiarize themselves with the software first.” 06/20/2008 NVIDIA, CUDA and PhysX EuroGamer “3D card manufacturers shouldn't take this the wrong way, but it takes a lot to make us crawl out of the communal Eurogamer bed (yes, all the Eurogamer writers share a single large bed - we do it for frugality and communality, which remain our watchwords) and go to a hardware presentation. There's a nagging fear someone may talk maths at us and we'd come home clutching the local equivalent of magic beans. And then we'll be laughed at by our fellow writers and made to sleep in the chilly end where the covers are thin and Tom left dubious stains. That's no fun at all.” 06/20/2008 NVIDIA's CUDA: The End of the CPU? Tom's Hardware CUDA is not a gimmick intended for researchers who want to cajole their university into buying them a GeForce. CUDA is genuinely usable by any programmer who knows C, provided he or she is ready to make a small investment of time and effort to adapt to this new programming paradigm. That effort won’t be wasted provided your algorithms lend themselves to parallelization. 06/18/2008 OptiTex to Use NVIDIA's CUDA Technology TenLinks.com "OptiTex' software is an ideal fit for NVIDIA as it leverages the combined personalities of our CUDA enabled GPUs - rich graphics and data intensive computation," said Andy Keane general manager of the GPU Computing business at NVIDIA. "OptiTex' software will deliver new levels of creative freedom for designers." 06/16/2008 NVIDIA Looking to Take Computing to the Next Level SFGate.com “NVIDIA released a new set of GPUs that not only boast a crazy amount of speed, but come with the promise of helping take on a larger set of tasks by delivering a lot more usable horsepower.” 06/16/2008 NVIDIA Releases 240-Core Graphics Processor eWeek.com “Tesla 10 series processor is Nvidia's latest offering for high-performance computing.” 06/16/2008 Nvidia and Stanford Finalizing Folding@Home Client for GeForce GPUs tgdaily “During Nvidia Editor's Day, we learned that Nvidia and the Folding@Home research group led by Vijay Pande are making final preparation to launch the first version of the Folding@Home client for Nvidia graphics processors.” 6/13/2008 Apple Eyeing NVIDIA's CUDA Technology? CNET “One of the most important performance challenges facing CUDA Apple's Worldwide Developers Conference is expected to cover the parallel tracks of Mac and iPhone software development, but the company may have another aspect of parallelism to discuss.” 06/06/2008 CUDA, Supercomputing for the Masses: Part 4 Dr.Dobb’s Portal “One of the most important performance challenges facing CUDA (short for "Compute Unified Device Architecture") developers is the best use of local multiprocessor memory resources such as shared memory, constant memory, and registers.” 06/03/2008 CUDA, Supercomputing for the Masses: Part 3 Dr.Dobb’s Portal “Congratulations! Thanks to Part 1 and Part 2 of this series on CUDA (short for "Compute Unified Device Architecture"), you are now a CUDA-enabled programmer with the ability to create and run programs that can use many hundreds of simultaneous threads on CUDA-enabled.” devices.” 05/13/08 Going to the Wall Advanced Imaging Magazine “Some jobs are just too big for one person, one company or one technology. In oil and gas exploration, for example, one seismic survey can equal 10 terabytes of data.” 05/15/08 CUDA and acceleration scalability.org “Took a Cuda class. Installed Cuda on my laptop. Well, 1.1 on my laptop. It has a Cuda class GPU (one of the things I made sure of when I bought it). 2.0 is in beta, and I think I will use that.” 05/13/08 | |||||||||||||||||||
