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CUDA CUDA (Compute Unified Device Architecture) is a parallel computing platform and programming model created by NVIDIA and implemented by the graphics processing units (GPUs) that they produce.[1] CUDA gives program developers direct access to the virtual instruction set and memory of the parallel computational elements in CUDA GPUs. Using CUDA, the GPUs can be used for general purpose processing (i.e., not exclusively graphics); this approach is known as GPGPU. Unlike CPUs, however, GPUs have a parallel throughput architecture that emphasizes executing many concurrent threads slowly, rather than executing a single thread very quickly. CALLIHOO Writing Helps Character Feelings You can describe your character's feelings in more exact terms than just "happy" or "sad." Check these lists for the exact nuance to describe your character's intensity of feelings. SF Characters | SF Items | SF Descriptors | SF Places | SF EventsSF Jobs/Occupations | Random Emotions | Emotions List | Intensity of Feelings

Artport Commissions: {Software} Structure » Open Software Structures » Open text about the project by Casey Reas The catalyst for this project is the work of Sol LeWitt, specifically his wall drawings. I had a simple question: "Is the history of conceptual art relevant to the idea of software as art?" I began to answer the question by implementing three of Lewitt's drawings in software and then making modifications. After working with the LeWitt plans, I created three structures unique to software.

Emacs Releases | Supported Platforms | Obtaining Emacs | Documentation | Support | Further information GNU Emacs is an extensible, customizable text editor—and more. At its core is an interpreter for Emacs Lisp, a dialect of the Lisp programming language with extensions to support text editing. The features of GNU Emacs include: OpenCL Open Computing Language (OpenCL) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors. OpenCL includes a language (based on C99) for writing kernels (functions that execute on OpenCL devices), plus application programming interfaces (APIs) that are used to define and then control the platforms. OpenCL provides parallel computing using task-based and data-based parallelism. OpenCL is an open standard maintained by the non-profit technology consortium Khronos Group. It has been adopted by Apple, Intel, Qualcomm, Advanced Micro Devices (AMD), Nvidia, Altera, Samsung, Vivante and ARM Holdings. For example, OpenCL can be used to give an application access to a graphics processing unit for non-graphical computing (see general-purpose computing on graphics processing units).

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Category Archives: Graphics 2D to 3DAstronomy | Anatomy series #2 | Anatomy Series #2 These 2D-3D graphics can be viewed with or without 3D Chromadepth glasses which can be purchase at Lillian Schwartz’s research began a number of years ago when she worked with art restorers in Italy to identify colors that had been lost in damaged art works, specifically frescoes by Piero Della Francesca. Working with individual pixels to determine the subtleties of the missing colors opened up other areas of study in anatomical structures, astronomical data obtained from telescopes, and her creations of the effects of global warming on our planet. The Python Standard Library While The Python Language Reference describes the exact syntax and semantics of the Python language, this library reference manual describes the standard library that is distributed with Python. It also describes some of the optional components that are commonly included in Python distributions. Python’s standard library is very extensive, offering a wide range of facilities as indicated by the long table of contents listed below.

GPGPU General-purpose computing on graphics processing units (GPGPU, rarely GPGP or GP²U) is the utilization of a graphics processing unit (GPU), which typically handles computation only for computer graphics, to perform computation in applications traditionally handled by the central processing unit (CPU).[1][2][3] Any GPU providing a functionally complete set of operations performed on arbitrary bits can compute any computable value. Additionally, the use of multiple graphics cards in one computer, or large numbers of graphics chips, further parallelizes the already parallel nature of graphics processing.[4] OpenCL is the currently dominant open general-purpose GPU computing language. The dominant proprietary framework is Nvidia's CUDA.[5] Programmability[edit] In principle, any boolean function can be built-up from a functionally complete set of logic operators.