CBLAS REFERENCE PDF

Basic Linear Algebra Subprograms BLAS is a specification that prescribes a set of low-level routines for performing common linear algebra operations such as vector addition, scalar multiplication , dot products , linear combinations, and matrix multiplication. They are the de facto standard low-level routines for linear algebra libraries; the routines have bindings for both C and Fortran. Although the BLAS specification is general, BLAS implementations are often optimized for speed on a particular machine, so using them can bring substantial performance benefits. Most libraries that offer linear algebra routines conform to the BLAS interface, allowing library users to develop programs that are agnostic of the BLAS library being used. ACML is no longer supported by its producer. MKL is a freeware [7] and proprietary [8] vendor library optimized for x86 and x with a performance emphasis on Intel processors.

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Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reservered for Intel microprocessors.

Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice. Safari Chrome IE Firefox. Add v? Sub v? Sqr v? Mul v? MulByConj v? Conj v? Abs v? Arg v? LinearFrac v? Fmod v? Remainder Power and Root Functions v?

Inv v? Div v? Sqrt v? InvSqrt v? Cbrt v? InvCbrt v? Pow2o3 v? Pow3o2 v? Pow v? Powx v? Powr v? Hypot Exponential and Logarithmic Functions v? Exp v? Exp2 v? Exp10 v? Expm1 v? Log2 v? Log10 v?

Log1p v? Logb Trigonometric Functions v? Cos v? Sin v? SinCos v? CIS v? Tan v? Acos v? Asin v? Atan v? Atan2 v? Cospi v? Sinpi v? Tanpi v? Acospi v? Asinpi v? Atanpi v? Atan2pi v? Cosd v? Sind v? Tand Hyperbolic Functions v? Cosh v? Sinh v? Tanh v? Acosh v? Asinh v? Atanh Special Functions v?

Erf v? Erfc v? CdfNorm v? ErfInv v? ErfcInv v? CdfNormInv v? LGamma v? TGamma v? ExpInt1 Rounding Functions v? Floor v? Ceil v? Trunc v? Round v? NearbyInt v? Rint v? Modf v? Pack v? CopySign v? NextAfter v? Fdim v? Fmax v? Fmin v? MaxMag v? EditPPSpline1D df? EditPtr dfiEditVal df? EditIdxPtr df? QueryPtr dfiQueryVal df? Construct1D df? InterpolateEx1D df? IntegrateEx1D df? SearchCellsEx1D df?

InterpCallBack df? IntegrCallBack df? Computes a matrix-vector product using a general matrix. Include Files.

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Basic Linear Algebra Subprograms

Any opinions, findings and conclusions or recommendations expressed in this material are those of the author s and do not necessarily reflect the views of the National Science Foundation NSF or the Department of Energy DOE. Discover the great history behind BLAS. On April an oral history interview was conducted as part of the SIAM project on the history of software for scientific computing and numerical analysis. This interview is being conducted with Professor Jack Dongarra in his office at the University of Tennessee.

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BLAS (Basic Linear Algebra Subprograms)

The browser version you are using is not recommended for this site. Please consider upgrading to the latest version of your browser by clicking one of the following links. Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain optimizations not specific to Intel microarchitecture are reservered for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more information regarding the specific instruction sets covered by this notice.

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The browser version you are using is not recommended for this site. Please consider upgrading to the latest version of your browser by clicking one of the following links. Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. Intel does not guarantee the availability, functionality, or effectiveness of any optimization on microprocessors not manufactured by Intel.

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The vecLib framework contains nine C header files not counting vec Lib. This document describes the functions declared in the header files cblas. Returns the index of the element with the largest absolute value in a vector single-precision complex. Returns the index of the element with the largest absolute value in a vector double-precision complex. Calculates the dot product of the complex conjugate of a single-precision complex vector with a second single-precision complex vector. Calculates the dot product of the complex conjugate of a double-precision complex vector with a second double-precision complex vector. Scales a general band matrix, then multiplies by a vector, then adds a vector single precision.

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