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YoGA features » Historique » Version 1

Damien Gratadour, 25/10/2013 09:24

1 1 Damien Gratadour
h1. YoGA features
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A list of features with corresponding wrappers is provided in the following. All these operations can be performed on a YoGA object. This webpage may not be up to date. Please refer to the file yoga.i for a complete list of available features. To get a full description of the syntax please use the help function in a Yorick session. 
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h2. General utilities
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*    extern _GetMaxGflopsDeviceId get the ID of the best CUDA-capable device on your system
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*    extern _setDeviceId set the active device to the specified ID
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*    func setDeviceId set the active device to the specified ID and returns its name
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*    extern _listDevice returns the list of CUDA-capable devices on your system
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*    extern _nbDevice returns the number of CUDA-capable devices on your system
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*    extern _yogaThreadExit exist threads on the active device
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*    extern _yogaThreadSync synchronizes threads on the active device
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*    extern _yogaInit init a YoGA session on the specified device
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*    extern _yogaInitCublas init a CUBLAS session on the active device
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*    extern _yogaShutdownCublas shutdown the CUBLAS session on the active device
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h2. Arrays manipulations
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*    extern yoga_obj creates an array on the GPU
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*    extern yoga_host2device fills an object on the GPU with data from the Yorick session
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*    extern yoga_device2host transfers data from an object on the GPU to the Yorick session
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*    extern yoga_setv create a new cublasVector from input data
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*    extern yoga_setm create a new cublasMatrix from input data
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*    extern yoga_getarray get a sub-array of input object specified by a range
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*    extern yoga_fillarray fill a sub-array of input object specified by a range
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*    extern yoga_getarray get the value of an array at specified position
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*    extern yoga_plus add a scalar to all the elements of an array
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*    extern yoga_plusai add a scalar (an element of a source array) to all the elements of an array
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h2. Matrix Operations
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YoGA provides support for most of the cublas functions as well as an autotuned custom tranpose method from the NVIDIA SDK.
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h3. BLAS functions
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*    extern yoga_imax returns the smallest index of the maximum magnitude element of obj
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*    extern yoga_imin returns the smallest index of the minimum magnitude element of obj
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*    extern yoga_asum retuns the sum of the absolute values of obj
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*    extern yoga_nrm2 returns the Euclidean norm of obj
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*    extern yoga_scale scales vectx by an amount specified by the second argument
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*    extern yoga_swap swaps the content of the 2 arguments