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CodeXL's GPU debugger allows engineers to debug OpenGL and OpenCL API calls and runtime objects, and debug OpenCL kernels: set breakpoints, step through source code in real-time, view all variables across different GPU cores during kernel execution, identify logic and memory errors, reduce memory transaction overhead, visualize OpenCL/OpenGL buffers and images and OpenGL textures as pictures ...
RenderDoc provides information of the calls on the GPU, the number of invocation of each shader, and the number of primitives and fragments generated. [ 9 ] Baldur Karlsson started RenderDoc development as a spare-time project out of need for a reliable debugger and was then expanded to support more platforms.
IBM Rational Purify was a memory debugger allowing performance analysis. Instruments (bundled with Xcode) is used to profile an executable's memory allocations, time usage, filesystem activity, GPU activity etc. Intel Parallel Studio contains Intel VTune Amplifier, which tunes both serial and parallel programs. It also includes Intel Advisor ...
GPU performance benchmarked on GPU supported features and may be a kernel to kernel performance comparison. For details on configuration used, view application website. Speedups as per Nvidia in-house testing or ISV's documentation. ‡ Q=Quadro GPU, T=Tesla GPU. Nvidia recommended GPUs for this application.
The libvdpau standalone VDPAU library is distributed by Nvidia independently of their proprietary Linux graphics driver in an effort to help the adoption of VDPAU by those outside of Nvidia. This open source library package contains a wrapper library and a debugging library allowing other manufacturers to implement VDPAU in their device drivers.
CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.
Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS. CUDA is able run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro.
PGI (formerly The Portland Group, Inc.) was a company that produced a set of commercially available Fortran, C and C++ compilers for high-performance computing systems. On July 29, 2013, Nvidia acquired The Portland Group, Inc. [1] [2] As of August 5, 2020, the "PGI Compilers and Tools" technology is a part of the Nvidia HPC SDK product available as a free download from Nvidia.