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nvidia corp (NVDA*) Details

NVIDIA Corporation operates as a visual computing company. The company operates through two segments, GPU and Tegra Processors. The GPU segment offers GeForce for consumer desktop and notebook personal computers; Quadro for professional workstations; Tesla for high-performance servers and workstations; and NVIDIA GRID for server graphics solutions. The Tegra Processors segment offers Tegra processors for smartphones, tablets, gaming devices, and other computer devices, such as Windows RT-based devices, set-top boxes, chromebooks, clamshells, and others; Icera baseband processors and radio frequency transceivers for mobile connectivity; Tegra NOTE, a tablet platform based on Tegra 4; Tegra VCM, a Tegra-based vehicle computing module that integrates an automotive computer into a single component; and SHIELD, an android gaming device for digital content in the cloud. The company’s products are used in gaming, design and visualization, high performance computing, data center, and automotive and smart device markets. NVIDIA Corporation sells its products to equipment manufacturers, original design manufacturers, system builders, motherboard manufacturers, and add-in board manufacturers in the United States, China, Taiwan, the rest of Asia Pacific, Europe, and other Americas. The company was founded in 1993 and is headquartered in Santa Clara, California.

8,808 Employees
Last Reported Date: 03/13/14
Founded in 1993

nvidia corp (NVDA*) Top Compensated Officers

Co-Founder, Chief Executive Officer, Presiden...
Total Annual Compensation: $837.5K
Chief Financial Officer and Executive Vice Pr...
Total Annual Compensation: $158.9K
Executive Vice President of Operations
Total Annual Compensation: $498.4K
Executive Vice President of Worldwide Field O...
Total Annual Compensation: $498.5K
Chief Administrative Officer, Executive Vice ...
Total Annual Compensation: $498.4K
Compensation as of Fiscal Year 2014.

nvidia corp (NVDA*) Key Developments

NVIDIA Announces Enhanced Version of Widely Used PGI Optimizing Compilers

NVIDIA announced that it is developing an enhanced version of the widely used PGI(R) optimizing compilers which will allow developers to quickly develop new applications or run Linux x86-based GPU-accelerated applications on IBM POWER CPU systems with minimal effort. The PGI optimizing Fortran, C and C++ compilers for POWER will provide a user interface, language features, parallel programming features and optimization capabilities that are identical to those available on PGI Linux x86 compilers. The new compilers also will support high performance computing (HPC) systems based on the IBM POWER architecture, including the recently announced NVIDIA GPU-accelerated IBM POWER8 systems, and additional systems under development by members of the OpenPOWER Foundation. The POWER8 CPU is a multi-threaded processor, featuring 12 cores each capable of handling eight hardware threads simultaneously. Originally positioned for big data and cloud server applications, the POWER8 architecture is generating strong demand from HPC customers given its many performance-oriented features, such as a high-bandwidth CAPI port (Coherent Accelerator Processor Interface) and future support for the NVLink(TM) high-speed GPU interconnect. Key features of the PGI compilers and tools for IBM POWER-based systems will include: OpenACC(R) directives for accelerators - Comprehensive support for OpenACC features in the PGI Accelerator native Fortran 2003, C11 and C++11 compilers on the latest generation of GPU accelerators from NVIDIA(R), including support for unified memory. PGI CUDA Fortran extensions - Feature parity with CUDA(R) Fortran on Linux/x86 platforms, offering the flexibility and power of the NVIDIA CUDA programming model in a native Fortran compiler for GPU-accelerated POWER systems. Faster OpenMP performance - PGI compilers deliver an average of 75% faster performance on the latest SPEC OMP2012 benchmark suite, compared to GCC 4.8 using the latest AVX-enabled multi-core x64 processors from Intel and AMD. PGI optimization features - Fortran 2003, C11 and C++11 compilers with the full range of PGI multi-core optimizations including comprehensive loop optimizations, memory hierarchy optimizations, SIMD vectorization, function inlining, inter-procedural analysis and optimization, profile feedback and more.

NVIDIA Unveils Accelerator for Data Analytics and Scientific Computing

NVIDIA unveiled a new addition to the NVIDIA Tesla Accelerated Computing Platform: the Tesla K80 dual-GPU accelerator, the world's high performance accelerator designed for a wide range of machine learning, data analytics, scientific, and high performance computing applications. The Tesla K80 dual-GPU is the new offering of the Tesla Accelerated Computing Platform, the platform for accelerating data analytics and scientific computing. It combines the world's fast GPU accelerators, the widely used CUDA parallel computing model, and a comprehensive ecosystem of software developers, software vendors, and datacenter system OEMs. The Tesla K80 dual-GPU accelerator delivers nearly two times higher performance and double the memory bandwidth of its predecessor, the Tesla K40 GPU accelerator. With ten times higher performance than today's fast CPU, it outperforms CPUs and competing accelerators on hundreds of complex analytics and large, computationally intensive scientific computing applications. Users can unlock the untapped performance of a broad range of applications with the accelerator's enhanced version of NVIDIA GPU Boost technology, which dynamically converts power headroom into the optimal performance boost for each individual application. The Tesla K80 dual-GPU accelerator was designed with the most difficult computational challenges in mind, ranging from astrophysics, genomics and quantum chemistry to data analytics. It is also optimized for advanced deep learning tasks, one of the fast growing segments of the machine learning field. The Tesla K80 delivers up to 8.74 teraflops single-precision and up to 2.91 teraflops double-precision peak floating point performance, and10 times higher performance than today's fast CPUs on science and engineering applications, such as AMBER, GROMACS, Quantum Espresso and LSMS. Key features of the Tesla K80 dual-GPU accelerator include: Two GPUs per board - Doubles throughput of applications designed to take advantage of multiple GPUs. 24GB of ultra-fast GDDR5 memory 12GB of memory per GPU, 2x more memory than Tesla K40 GPU, allows users to process 2x larger datasets. 480GB/s memory bandwidth - Increased data throughput allows data scientists to crunch though petabytes of information in half the time compared to the Tesla K10 accelerator. Optimized for energy exploration, video and image processing, and data analytics applications. 4,992 CUDA(R) parallel processing cores - Accelerates applications by up to 10x compared to using a CPU alone. Dynamic NVIDIA GPU Boost Technology Dynamically scales GPU clocks based on the characteristics of individual applications for maximum performance. Dynamic Parallelism Enables GPU threads to dynamically spawn new threads, enabling users to quickly and easily crunch through adaptive and dynamic data structures.

The U.S. Department of Energy to Build Two Supercomputers for National Labs Using IBM Power Servers with NVIDIA Tesla GPU Accelerators and NVIDIA NVLink GPU Interconnect Technology

The U.S. Department of Energy unveiled plans to build two GPU-accelerated supercomputers expected to deliver at least three-times greater performance than present most powerful system, which will move the world closer to the long-held goal of exascale computing. The supercomputers, to be installed in 2017, will be based on next-generation IBM POWER servers with NVIDIA(R) Tesla(R) GPU accelerators and NVIDIA NVLink(TM) high-speed GPU interconnect technology. The Summit system at Oak Ridge National Laboratory will be capable of delivering 150 to 300 peak petaflops, and be used for open science. Delivering performance well in excess of 100 peak petaflops, the Sierra system will be a key element of Lawrence Livermore National Laboratory's national nuclear security mission. They will be considerably faster than the U.S.'s current speed champ, Oak Ridge's Titan, which delivers 27 peak petaflops, as well as the fast, Tianhe-2 at China's National Super Computer Center, in Guangzhou, which delivers 55 peak petaflops. The systems represent the first major milestone in the ongoing partnership between IBM and NVIDIA. They build upon the work of the OpenPOWER Foundation, an open development community formed to develop next-generation computing solutions for high performance computing and enterprise data center customers. The supercomputing community has for many years worked toward building exascale systems, which can perform a quintillion a billion billion or 10(18) floating point calculations per second, known as FLOPS. A FLOP is equivalent to a single mathematical calculation, like multiplying two numbers together. Summit and Sierra will be the next major step on the path to reaching exascale computing levels by virtue of a number of breakthrough technologies. One is the NVIDIA NVLink high-speed GPU interconnect, which will be integrated into NVIDIA GPUs and IBM POWER CPUs powering the new systems. NVLink allows GPUs and CPUs to share data five to 12 times faster than today, and is designed to ultimately enable supercomputers that are 50 to 100 times faster than today's fastest systems. The systems will also feature NVIDIA's future generation GPU architecture, Volta, which will deliver considerably higher performance than the company's current Maxwell(TM) architecture and subsequent Pascal design. Delivering significantly higher levels of computational performance than anything available today, NVIDIA GPUs will provide Summit and Sierra with more than 90% of the peak floating point processing capability.


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