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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.
Open core: Full version under Apache License 2.0: Yes Yes Yes Unknown Yes Yes (full version only) Yes (full version only) Yes Yes PEP 8 and others Yes Yes Yes Yes Yes PyDev / LiClipse (plug-in for Eclipse and Aptana) Appcelerator: 7.5.0 2020-01-10 Windows, Linux, macOS, FreeBSD, JVM, Solaris: Python: SWT: EPL: Yes Yes
The initial CUDA SDK was made public on 15 February 2007, for Microsoft Windows and Linux. Mac OS X support was later added in version 2.0, [18] which supersedes the beta released February 14, 2008. [19] CUDA works with all Nvidia GPUs from the G8x series onwards, including GeForce, Quadro and the Tesla line. CUDA is compatible with most ...
MontaVista DevRocket, plug-in to Eclipse; MyEclipse, from Genuitec is an IDE which also enables Angular Typescript development from within the Java-Eclipse platform using its Webclipse plug-in and Angular IDE solution. [buzzword] Nuxeo RCP, an open source rich client platform for ECM applications. OEPE, Oracle Enterprise Pack for Eclipse.
A 1.3 level Java runtime or Java development kit must be installed on the machine in order to run this version of Eclipse. [28] N/A: 18 September 2002 [29] 2.0 N/A: 15 April 2003 [30] 2.1 A 1.4 level Java runtime or Java development kit (JDK) can also be used to run Eclipse.
However it integrated editing, file management, compilation, debugging and execution in a manner consistent with a modern IDE. Maestro I is a product from Softlab Munich and was the world's first integrated development environment [1] for software. Maestro I was installed for 22,000 programmers worldwide.
rCUDA, which stands for Remote CUDA, is a type of middleware software framework for remote GPU virtualization. Fully compatible with the CUDA application programming interface ( API ), it allows the allocation of one or more CUDA-enabled GPUs to a single application.
C2050 GPU Computing Module [11] Fermi: July 25, 2011 1× GF100 575 448 1150 — GDDR5 384 3 [g] 3000 144 No 1.030 0.5152 2.0 247 Internal PCIe GPU (full-height, dual-slot) M2050 GPU Computing Module [12] July 25, 2011 — 3092 148.4 No 225 C2070 GPU Computing Module [11] July 25, 2011 1× GF100 575 448 1150 — GDDR5 384 6 [g] 3000 144 No 1.030 ...