ACADEMIA

New NVIDIA Computing Architecture Enables Data Processing on the GPU for Next- Generation Commercial Applications, Technical Computing, and Advanced Gaming: NVIDIA Corporation unveiled NVIDIA CUDA technology, a fundamentally new architecture for computing on NVIDIA graphics processing units (GPUs), and the industry's first C-compiler development environment for the GPU. GPU computing with CUDA is a new approach to computing where hundreds of on-chip processor cores simultaneously communicate and cooperate to solve complex computing problems up to 100 times faster than traditional approaches. This breakthrough architecture is complemented by another first -- the NVIDIA C-compiler for the GPU. This complete development environment gives developers the tools they need to solve new problems in computation-intensive applications such as product design, data analysis, technical computing, and game physics. Available today on the new GeForce 8800 graphics card and future NVIDIA Quadro Professional Graphics solutions, computing with CUDA transcends the limitations of traditional GPU stream computing by enabling GPU processor cores to communicate, synchronize, and share data. "Our customers, including every cell phone manufacturer in the world, see the value in using NVIDIA GPUs with Acceleware's GPU-accelerated solver, to speed up their time to market," said Dr. Nicolas Chavannes, director software for Schmid and Partner Engineering AG (SPEAG). "The level of computing performance now achievable with CUDA-enabled GPUs, will positively impact our customers' bottom lines." CUDA-enabled GPUs offer dedicated features for computing, including the Parallel Data Cache, which allows 128, 1.35GHz processor cores in newest generation NVIDIA GPUs to cooperate with each other while performing intricate computations. Developers access these new features through a separate computing driver that communicates with DirectX and OpenGL, and the new NVIDIA C compiler for the GPU, which obsoletes streaming languages for GPU computing. A CUDA-enabled GPU operates as either a flexible thread processor, where thousands of computing programs called threads work together to solve complex problems, or as a streaming processor in specific applications such as imaging where threads do not communicate. CUDA-enabled applications use the GPU for fine grained data-intensive processing, and the multi-core CPUs for complicated coarse grained tasks such as control and data management. "CUDA gives us a whole new level of computing capability and enables closer access to the hardware," said Ryan Schneider, CTO of Acceleware Corp. "CUDA makes it possible for Acceleware's electromagnetic simulation and geophysical processing products to continue to double in speed each year, and, with our OEM partners like SPEAG, will enable us to address the needs of new markets such as biomedical imaging and reservoir modeling. The latest advancements from NVIDIA are helping to quickly push the boundaries of product development and commercial science." "CUDA opens the door for new ways to analyze and interpret seismic data, allowing for interaction with multi-terabyte prestack surveys," says Alex Krueger, president of Headwave, Inc. "With this compelling new GPU architecture from NVIDIA, we can accelerate some of the most computationally intensive algorithms in oil and gas exploration -- far beyond the performance CPUs are capable of delivering." The CUDA Software Developers Kit (SDK) is currently available to developers and researchers through the NVIDIA registered developer program. For more details on developing with CUDA, visit the NVIDIA its Web site.