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Deep Learning on the NVIDIA Developer Zone

Developer resources for deep learning, deep neural networks, and more. Find research, presentations, articles, educational links, events, and more.
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Unified Memory: Now for CUDA Fortran Programmers

Unified Memory: Now for CUDA Fortran Programmers | EEDSP | Scoop.it
Unified Memory is a CUDA feature that we've talked a lot about on Parallel Forall. CUDA 6 introduced Unified Memory, which dramatically simplifies GPU programming by giving programmers a single poi...
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CUDA Pro Tip: Profiling MPI Applications

CUDA Pro Tip: Profiling MPI Applications | EEDSP | Scoop.it

When I profile a MPI+CUDA application sometimes performance issues only occur for certain MPI ranks. To fix these, it's necessary to identify the MPI rank where the performance issue occurs. Up to ...

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Deep learning with COTS HPC systems

Deep learning with COTS HPC systems | EEDSP | Scoop.it
Scaling up deep learning algorithms has been shown to lead to increased performance in benchmark tasks and to enable discovery of complex high-level features. Recent efforts to train extremely larg...
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CUDA Toolkit | CUDA 6 Production Release

The NVIDIA® CUDA® Toolkit provides a comprehensive development environment for C and C++ developers building GPU-accelerated applications. The CUDA Toolkit includes a compiler for NVIDIA GPUs, math libraries, and tools for debugging and optimizing the performance of your applications.
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CUDA 6, Available as Free Download, Makes Parallel Programming Easier, Faster

CUDA 6, Available as Free Download, Makes Parallel Programming Easier, Faster | EEDSP | Scoop.it

Available now to all developers on the CUDA website, the CUDA 6 Release Candidate is packed with several new features that are sure to please developers

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NVIDIA Announces CUDA 6: Unified Memory for CUDA

NVIDIA Announces CUDA 6: Unified Memory for CUDA | EEDSP | Scoop.it

The big news here – and the headlining feature for CUDA 6 – is that NVIDIA has implemented complete unified memory support within CUDA. The toolkit has possessed unified virtual addressing support since CUDA 4, allowing the disparate x86 and GPU memory pools to be addressed together in a single space. But unified virtual addressing only simplified memory management; it did not get rid of the required explicit memory copying and pinning operations necessary to bring over data to the GPU first before the GPU could work on it.

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NVIDIA and Continuum Analytics Announce NumbaPro, A Python CUDA Compiler

NVIDIA and Continuum Analytics Announce NumbaPro, A Python CUDA Compiler | EEDSP | Scoop.it

As NVIDIA’s GPU Technology Conference 2013 kicks off this week, there will be a number of announcements coming down the pipeline from NVIDIA and their partners. The biggest and more important of these announcements will be Tuesday morning with NVIDIA CEO’s Jen-Hsun Huang’s keynote speech, while some other product announcements such as this one are being released today with the start of the show.

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CUDA 5 Production Release Now Available :: GPGPU.org

The CUDA 5 Production Release is now available as a free download at www.nvidia.com/getcuda.

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10 Ways CUDA 6.5 Improves Performance and Productivity

10 Ways CUDA 6.5 Improves Performance and Productivity | EEDSP | Scoop.it
Today we're excited to announce the release of the CUDA Toolkit version 6.5. CUDA 6.5 adds a number of features and improvements to the CUDA platform, including support for CUDA Fortran in develope...
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Accelerate R Applications with CUDA

Accelerate R Applications with CUDA | EEDSP | Scoop.it

In this article, I will introduce the computation model of R with GPU acceleration, focusing on three topics:

accelerating R computations using CUDA libraries;calling your own parallel algorithms written in CUDA C/C++ or CUDA Fortran from R; andprofiling GPU-accelerated R applications using the CUDA Profiler.

 

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NVIDIA GPUs Deliver a Shot in the ARM for HPC Industry

NVIDIA GPUs Deliver a Shot in the ARM for HPC Industry | EEDSP | Scoop.it
Among the most interesting announcements at this week’s ISC’14 is the emergence of a new class of system – one that marries the many advantages of ARM processors with the massively parallel processing power of NVIDIA Tesla GPU accelerators. This is great news for the industry. Initially designed for micro-servers and web servers, ARM64 server processors… Read More
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CUDA Spotlight: GPU-Accelerated Deep Learning

CUDA Spotlight: GPU-Accelerated Deep Learning | EEDSP | Scoop.it

Our Spotlight is on Dr. Ren Wu, a distinguished scientist at Baidu's Institute of Deep Learning (IDL). He is known for his pioneering research in using GPUs to accelerate big data analytics and his...

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The CUDA Thrust API Now Supports Streams and Concurrent Tasks

The CUDA Thrust API Now Supports Streams and Concurrent Tasks | EEDSP | Scoop.it
The CUDA Thrust API now supports streams and concurrent kernels through the use of a new API called Bulk created by Jared Hoberock at NVIDIA. The design of Bulk is intended to extend the parallel e...
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CUDA Spotlight: GPU-Accelerated Speech Recognition

CUDA Spotlight: GPU-Accelerated Speech Recognition | EEDSP | Scoop.it
This week's Spotlight is on Dr. Ian Lane of Carnegie Mellon University. Ian is an Assistant Research Professor and leads a speech and language processing research group based in Silicon Valley. He ...
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Topiary eDiscovery LLC's curator insight, March 12, 2014 10:30 AM

Carnegie Mellon... the Incubator.

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How New Features in CUDA 6 Make GPU Acceleration Easier - insideHPC

In this video from the Nvidia booth at SC13, Mark Harris from Nvidia presents: New Features in CUDA 6 Make GPU Acceleration Easier.
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Permutations with CUDA and OpenCL - CodeProject®

Finding lexicographical permutations using GPU; Author: Wong Shao Voon; Updated: 8 May 2012; Section: GPU Programming; Chapter: Platforms, Frameworks & Libraries; Updated: 8 May 2012...
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