The second big feature coming to Parallel Nsight 1.5 will be the addition of support for debugging code on a GPU running in Tesla Compute Cluster (TCC) mode. However at this time this single-system debugging support only applies to compute shader debugging still requires a second system. In this case the GPUs don’t even need to match so long as it's an NVIDIA GPU, allowing developers to use a high-end GPU for programming purposes while using a lesser GPU to drive the display, effectively halving the amount of hardware required for debugging. This allows one GPU to run the application, and then a second GPU to actually drive the computer’s display. While this is still (and likely always will be) the preferred method of debugging, it was impractical for single developers and smaller shops that couldn’t dedicate a second machine to the task.įor those programmers, Parallel Nsight 1.5 will be adding support for debugging compute code within a single system when multiple GPUs are present. Because the GPU needs to maintain the compute or graphics context being debugged, the only way to do debugging was to have a second system or a virtualized system to work with – one system to actually run the code, and a second system to debug from. On the backend of things, Parallel Nsight 1.5 will be expanding the debugging capabilities of the plugin, particularly on single-system scenarios. Previously Parallel Nsight only supported VS 2008, which left Parallel Nsight behind as companies and developers began switching to Visual Studio 2010. Headlining this launch is the inclusion of Visual Studio 2010 support, bringing Parallel Nsight up to date with Microsoft’s IDE. On Wednesday the 22 nd NVIDIA will be releasing the first major update to Parallel Nsight with release 1.5 of the plugin. Since then roughly 8,000 developers have signed up to use the plugin. We first saw Parallel Nsight last year when Fermi was introduced under the name Nexus, and it finally shipped a few months ago along-side the first Fermi based Tesla cards. In order to accomplish this goal, NVIDIA wrote a plugin for Visual Studio to enable the complete programming and debugging of CUDA and graphics code within Visual Studio – something that wasn’t previously possible – called Parallel Nsight. Reaching these programmers would require extending CUDA programming to the IDE and toolsets they already use, and in the process expand the market by making development more accessible than it was with older toolsets. Furthermore NVIDIA ultimately wants to extend practical GPU programming to the more rank & file programmers, where Microsoft’s Visual Studio is by far and wide the IDE of choice for C and C++. With support for higher level languages comes the need for better programming tools and better debugging tools. ![]() However good hardware requires good software, and that’s where our discussion is going today. ![]() With the Fermi architecture NVIDIA would have the hardware necessary to take the next step in to GPU computing. The Fermi architecture was a big step towards this goal, providing a GPU much better suited for GPU computing than the previous GT200/G80 thanks in large part to the GPU’s unified address space, ECC support, and support for C++. Specifically, they will be releasing Parallel Nsight 1.5, and version 3.2 of the CUDA Toolkit.Īs we’ve reiterated a number of times now, NVIDIA’s long-term goals require the company to expand their GPU market beyond video cards and in to the High Performance Computing (HPC) space, where the brute force applied by GPUs for gaming purposes can be applied to academic, industrial, and even consumer computing applications. Next week NVIDIA will be releasing the first major update to their GPGPU programming toolchain since the Fermi-based Tesla series launched earlier this year. Not to be outdone by Intel’s IDF and AMD’s counter-meeting this week, NVIDIA’s GPU Computing group has their own announcement this week ahead of their GPU Technology Conference next week.
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