Showing posts with label Nvidia. Show all posts
Showing posts with label Nvidia. Show all posts

Tuesday, August 7, 2012

Chinese Researchers Program Tesla GPUs with OpenACC


NVIDIA today announced that the OpenACC programming standard has enabled Chinese researchers to dramatically accelerate the DNADist genomics application,1 which is used in the early stages of development of treatments for genetic conditions, such as Down syndrome, hemophilia, cystic fibrosis, and sickle-cell disease.



Using the CAPS enterprise OpenACC compiler, Shanghai Jia Tong University researchers accelerated the DNADist application by 16 times on an NVIDIA® Tesla® GPU-based system by adding just four simple hints -- known as "directives" -- to the application code.

DNADist, a distance-matrix application for studying the genetic relationships between various species over evolutionary history, enables researchers to extract information from sequenced DNA data by reading nucleotide sequences, which may potentially lead to a greater understanding of the causes of and treatments for pervasive genetic diseases. Accelerating the DNADist application allows researchers to study a significantly larger range of input data and obtain actionable information earlier in the disease treatment research process.

A programming standard for parallel computing using directives, OpenACC is designed to enable millions of researchers around the world to easily take advantage of the transformative power of GPU computing. It provides the easiest way for users, with or without extensive parallel programming expertise, to accelerate their research in a matter of hours using familiar programming models.

Roche Impressed with OpenACC, Power of GPU Acceleration
By quickly delivering game-changing application acceleration with minimal effort, OpenACC provides world-leading pharmaceutical companies like Roche with the ability to research, identify and develop more effective drugs faster and more cost-effectively.

"I am astonished at how quickly and easily OpenACC unlocked the power of GPU acceleration for DNADist, which is one of our most critical applications," said Steve Pan, project director, Roche Pharma Global Informatics. "The potential impact of GPUs is priceless because getting our products to market faster, even one day earlier, will save more lives."

"Extracting meaningful information from the vast collection of available DNA sequencing data requires ever-increasing amounts of computational power," said Sumit Gupta, senior director of the Tesla business at NVIDIA. "OpenACC enables researchers to quickly and easily leverage the enormous performance of GPU accelerators to analyze mountains of genomics data. This dramatically reduces the time to study biological systems, and potentially leads to the development of more effective next-generation medicines."

A large and growing number of researchers and engineers are using OpenACC-supported compilers and hybrid CPU/GPU computing systems to accelerate all types of applications, including CAD/CAM, image processing, materials science, molecular dynamics, quantum chemistry, and many other applications. In many cases, users are reporting that they have achieved as much as 5-10X or faster levels of acceleration in as little as a few hours of work.

Thursday, May 10, 2012

Nvidia contributes CUDA compiler to open source


Nvidia has announced that the LLVM, a popular open source compiler, now supports its GPUs. The company worked with LLVM developers to provide the CUDA compiler source code changes to the LLVM core and parallel thread execution backend. As a result, programmers can develop applications for GPU accelerators using a broader selection of programming languages, the company said.

LLVM is a widely used open source compiler infrastructure, with a modular design that makes it easy to add support for programming languages and processor architectures. The CUDA compiler provides C, C++ and Fortran support for accelerating application using the Nvidia GPUs.

LLVM supports a wide range of programming languages and front ends, including C/C++, Objective-C, Fortran, Ada, Haskell, Java bytecode, Python, Ruby, ActionScript, GLSL and Rust. It is also the compiler infrastructure Nvidia uses for its CUDA C/C++ architecture, and it has been widely adopted by companies such as Apple, AMD and Adobe.

"The code we provided to LLVM is based on proven, mainstream CUDA products, giving programmers the assurance of reliability and full compatibility with the hundreds of millions of Nvidia GPUs installed in PCs and servers today," said Ian Buck, general manager, GPU computing software, Nvidia.