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210 lines
25 KiB
Python
Executable file
210 lines
25 KiB
Python
Executable file
#!/usr/bin/env python
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# This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This file follows the
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# PEP8 Python style guide and uses a max-width of 120 characters per line.
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#
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# Author(s):
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# Cedric Nugteren <www.cedricnugteren.nl>
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#
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# This script automatically generates the bodies of the following files, creating the full CLBlast API interface and
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# implementation (C, C++, and reference BLAS wrappers):
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# clblast.h
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# clblast.cpp
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# clblast_c.h
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# clblast_c.cpp
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# wrapper_clblas.h
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# wrapper_cblas.h
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# It also generates the main functions for the correctness and performance tests as found in
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# test/correctness/routines/levelX/xYYYY.cpp
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# test/performance/routines/levelX/xYYYY.cpp
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# It also produces the API documentation found in doc/clblast.md
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import sys
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import os.path
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import argparse
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import generator.cpp as cpp
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import generator.doc as doc
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from generator.routine import Routine
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from generator.datatype import H, S, D, C, Z, Sc, Dz, iH, iS, iD, iC, iZ, Css, Zdd, Ccs, Zzd, T, Tc, TU
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FILES = [
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"/include/clblast.h",
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"/src/clblast.cpp",
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"/include/clblast_c.h",
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"/src/clblast_c.cpp",
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"/test/wrapper_clblas.hpp",
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"/test/wrapper_cblas.hpp",
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]
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HEADER_LINES = [117, 73, 118, 22, 29, 41]
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FOOTER_LINES = [17, 80, 19, 18, 6, 6]
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# Different possibilities for requirements
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ald_m = "The value of `a_ld` must be at least `m`."
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ald_n = "The value of `a_ld` must be at least `n`."
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ald_k_one = "The value of `a_ld` must be at least `k + 1`."
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ald_kl_ku_one = "The value of `a_ld` must be at least `kl + ku + 1`."
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ald_transa_m_k = "When `transpose_a == Transpose::kNo`, then `a_ld` must be at least `m`, otherwise `a_ld` must be at least `k`."
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ald_trans_n_k = "When `transpose == Transpose::kNo`, then `a_ld` must be at least `n`, otherwise `a_ld` must be at least `k`."
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ald_side_m_n = "When `side = Side::kLeft` then `a_ld` must be at least `m`, otherwise `a_ld` must be at least `n`."
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bld_m = "The value of `b_ld` must be at least `m`."
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bld_n = "The value of `b_ld` must be at least `n`."
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bld_transb_k_n = "When `transpose_b == Transpose::kNo`, then `b_ld` must be at least `k`, otherwise `b_ld` must be at least `n`."
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bld_trans_n_k = "When `transpose == Transpose::kNo`, then `b_ld` must be at least `n`, otherwise `b_ld` must be at least `k`."
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cld_m = "The value of `c_ld` must be at least `m`."
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cld_n = "The value of `c_ld` must be at least `n`."
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# ==================================================================================================
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# Populates a list of routines
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ROUTINES = [
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[ # Level 1: vector-vector
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Routine(False, True, "1", "rotg", T, [S,D], [], [], [], ["sa","sb","sc","ss"], [], "", "Generate givens plane rotation", "", []),
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Routine(False, True, "1", "rotmg", T, [S,D], [], [], ["sy1"], ["sd1","sd2","sx1","sparam"], [], "", "Generate modified givens plane rotation", "", []),
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Routine(False, True, "1", "rot", T, [S,D], ["n"], [], [], ["x","y"], ["cos","sin"], "", "Apply givens plane rotation", "", []),
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Routine(False, True, "1", "rotm", T, [S,D], ["n"], [], [], ["x","y","sparam"], [], "", "Apply modified givens plane rotation", "", []),
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Routine(True, True, "1", "swap", T, [S,D,C,Z,H], ["n"], [], [], ["x","y"], [], "", "Swap two vectors", "Interchanges _n_ elements of vectors _x_ and _y_.", []),
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Routine(True, True, "1", "scal", T, [S,D,C,Z,H], ["n"], [], [], ["x"], ["alpha"], "", "Vector scaling", "Multiplies _n_ elements of vector _x_ by a scalar constant _alpha_.", []),
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Routine(True, True, "1", "copy", T, [S,D,C,Z,H], ["n"], [], ["x"], ["y"], [], "", "Vector copy", "Copies the contents of vector _x_ into vector _y_.", []),
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Routine(True, True, "1", "axpy", T, [S,D,C,Z,H], ["n"], [], ["x"], ["y"], ["alpha"], "", "Vector-times-constant plus vector", "Performs the operation _y = alpha * x + y_, in which _x_ and _y_ are vectors and _alpha_ is a scalar constant.", []),
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Routine(True, True, "1", "dot", T, [S,D,H], ["n"], [], ["x","y"], ["dot"], [], "n", "Dot product of two vectors", "Multiplies _n_ elements of the vectors _x_ and _y_ element-wise and accumulates the results. The sum is stored in the _dot_ buffer.", []),
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Routine(True, True, "1", "dotu", T, [C,Z], ["n"], [], ["x","y"], ["dot"], [], "n", "Dot product of two complex vectors", "See the regular xDOT routine.", []),
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Routine(True, True, "1", "dotc", T, [C,Z], ["n"], [], ["x","y"], ["dot"], [], "n", "Dot product of two complex vectors, one conjugated", "See the regular xDOT routine.", []),
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Routine(True, True, "1", "nrm2", T, [S,D,Sc,Dz,H], ["n"], [], ["x"], ["nrm2"], [], "2*n", "Euclidian norm of a vector", "Accumulates the square of _n_ elements in the _x_ vector and takes the square root. The resulting L2 norm is stored in the _nrm2_ buffer.", []),
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Routine(True, True, "1", "asum", T, [S,D,Sc,Dz,H], ["n"], [], ["x"], ["asum"], [], "n", "Absolute sum of values in a vector", "Accumulates the absolute value of _n_ elements in the _x_ vector. The results are stored in the _asum_ buffer.", []),
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Routine(True, False, "1", "sum", T, [S,D,Sc,Dz,H], ["n"], [], ["x"], ["sum"], [], "n", "Sum of values in a vector (non-BLAS function)", "Accumulates the values of _n_ elements in the _x_ vector. The results are stored in the _sum_ buffer. This routine is the non-absolute version of the xASUM BLAS routine.", []),
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Routine(True, True, "1", "amax", T, [iS,iD,iC,iZ,iH], ["n"], [], ["x"], ["imax"], [], "2*n", "Index of absolute maximum value in a vector", "Finds the index of the maximum of the absolute values in the _x_ vector. The resulting integer index is stored in the _imax_ buffer.", []),
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Routine(True, False, "1", "max", T, [iS,iD,iC,iZ,iH], ["n"], [], ["x"], ["imax"], [], "2*n", "Index of maximum value in a vector (non-BLAS function)", "Finds the index of the maximum of the values in the _x_ vector. The resulting integer index is stored in the _imax_ buffer. This routine is the non-absolute version of the IxAMAX BLAS routine.", []),
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Routine(True, False, "1", "min", T, [iS,iD,iC,iZ,iH], ["n"], [], ["x"], ["imin"], [], "2*n", "Index of minimum value in a vector (non-BLAS function)", "Finds the index of the minimum of the values in the _x_ vector. The resulting integer index is stored in the _imin_ buffer. This routine is the non-absolute minimum version of the IxAMAX BLAS routine.", []),
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],
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[ # Level 2: matrix-vector
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Routine(True, True, "2a", "gemv", T, [S,D,C,Z,H], ["m","n"], ["layout","a_transpose"], ["a","x"], ["y"], ["alpha","beta"], "", "General matrix-vector multiplication", "Performs the operation _y = alpha * A * x + beta * y_, in which _x_ is an input vector, _y_ is an input and output vector, _A_ is an input matrix, and _alpha_ and _beta_ are scalars. The matrix _A_ can optionally be transposed before performing the operation.", [ald_m]),
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Routine(True, True, "2a", "gbmv", T, [S,D,C,Z,H], ["m","n","kl","ku"], ["layout","a_transpose"], ["a","x"], ["y"], ["alpha","beta"], "", "General banded matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is banded instead.", [ald_kl_ku_one]),
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Routine(True, True, "2a", "hemv", T, [C,Z], ["n"], ["layout","triangle"], ["a","x"], ["y"], ["alpha","beta"], "", "Hermitian matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is an Hermitian matrix instead.", [ald_n]),
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Routine(True, True, "2a", "hbmv", T, [C,Z], ["n","k"], ["layout","triangle"], ["a","x"], ["y"], ["alpha","beta"], "", "Hermitian banded matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is an Hermitian banded matrix instead.", [ald_k_one]),
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Routine(True, True, "2a", "hpmv", T, [C,Z], ["n"], ["layout","triangle"], ["ap","x"], ["y"], ["alpha","beta"], "", "Hermitian packed matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is an Hermitian packed matrix instead and represented as _AP_.", []),
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Routine(True, True, "2a", "symv", T, [S,D,H], ["n"], ["layout","triangle"], ["a","x"], ["y"], ["alpha","beta"], "", "Symmetric matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is symmetric instead.", [ald_n]),
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Routine(True, True, "2a", "sbmv", T, [S,D,H], ["n","k"], ["layout","triangle"], ["a","x"], ["y"], ["alpha","beta"], "", "Symmetric banded matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is symmetric and banded instead.", [ald_k_one]),
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Routine(True, True, "2a", "spmv", T, [S,D,H], ["n"], ["layout","triangle"], ["ap","x"], ["y"], ["alpha","beta"], "", "Symmetric packed matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is a symmetric packed matrix instead and represented as _AP_.", []),
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Routine(True, True, "2a", "trmv", T, [S,D,C,Z,H], ["n"], ["layout","triangle","a_transpose","diagonal"], ["a"], ["x"], [], "n", "Triangular matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is triangular instead.", [ald_n]),
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Routine(True, True, "2a", "tbmv", T, [S,D,C,Z,H], ["n","k"], ["layout","triangle","a_transpose","diagonal"], ["a"], ["x"], [], "n", "Triangular banded matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is triangular and banded instead.", [ald_k_one]),
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Routine(True, True, "2a", "tpmv", T, [S,D,C,Z,H], ["n"], ["layout","triangle","a_transpose","diagonal"], ["ap"], ["x"], [], "n", "Triangular packed matrix-vector multiplication", "Same operation as xGEMV, but matrix _A_ is a triangular packed matrix instead and repreented as _AP_.", []),
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Routine(False, True, "2a", "trsv", T, [S,D,C,Z], ["n"], ["layout","triangle","a_transpose","diagonal"], ["a"], ["x"], [], "", "Solves a triangular system of equations", "", []),
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Routine(False, True, "2a", "tbsv", T, [S,D,C,Z], ["n","k"], ["layout","triangle","a_transpose","diagonal"], ["a"], ["x"], [], "", "Solves a banded triangular system of equations", "", [ald_k_one]),
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Routine(False, True, "2a", "tpsv", T, [S,D,C,Z], ["n"], ["layout","triangle","a_transpose","diagonal"], ["ap"], ["x"], [], "", "Solves a packed triangular system of equations", "", []),
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# Level 2: matrix update
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Routine(True, True, "2b", "ger", T, [S,D,H], ["m","n"], ["layout"], ["x","y"], ["a"], ["alpha"], "", "General rank-1 matrix update", "Performs the operation _A = alpha * x * y^T + A_, in which _x_ is an input vector, _y^T_ is the transpose of the input vector _y_, _A_ is the matrix to be updated, and _alpha_ is a scalar value.", [ald_m]),
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Routine(True, True, "2b", "geru", T, [C,Z], ["m","n"], ["layout"], ["x","y"], ["a"], ["alpha"], "", "General rank-1 complex matrix update", "Same operation as xGER, but with complex data-types.", [ald_m]),
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Routine(True, True, "2b", "gerc", T, [C,Z], ["m","n"], ["layout"], ["x","y"], ["a"], ["alpha"], "", "General rank-1 complex conjugated matrix update", "Same operation as xGERU, but the update is done based on the complex conjugate of the input vectors.", [ald_m]),
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Routine(True, True, "2b", "her", Tc, [Css,Zdd], ["n"], ["layout","triangle"], ["x"], ["a"], ["alpha"], "", "Hermitian rank-1 matrix update", "Performs the operation _A = alpha * x * x^T + A_, in which x is an input vector, x^T is the transpose of this vector, _A_ is the triangular Hermetian matrix to be updated, and alpha is a scalar value.", [ald_n]),
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Routine(True, True, "2b", "hpr", Tc, [Css,Zdd], ["n"], ["layout","triangle"], ["x"], ["ap"], ["alpha"], "", "Hermitian packed rank-1 matrix update", "Same operation as xHER, but matrix _A_ is an Hermitian packed matrix instead and represented as _AP_.", []),
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Routine(True, True, "2b", "her2", T, [C,Z], ["n"], ["layout","triangle"], ["x","y"], ["a"], ["alpha"], "", "Hermitian rank-2 matrix update", "Performs the operation _A = alpha * x * y^T + conj(alpha) * y * x^T + A_, in which _x_ is an input vector and _x^T_ its transpose, _y_ is an input vector and _y^T_ its transpose, _A_ is the triangular Hermetian matrix to be updated, _alpha_ is a scalar value and _conj(alpha)_ its complex conjugate.", [ald_n]),
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Routine(True, True, "2b", "hpr2", T, [C,Z], ["n"], ["layout","triangle"], ["x","y"], ["ap"], ["alpha"], "", "Hermitian packed rank-2 matrix update", "Same operation as xHER2, but matrix _A_ is an Hermitian packed matrix instead and represented as _AP_.", []),
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Routine(True, True, "2b", "syr", T, [S,D,H], ["n"], ["layout","triangle"], ["x"], ["a"], ["alpha"], "", "Symmetric rank-1 matrix update", "Same operation as xHER, but matrix A is a symmetric matrix instead.", [ald_n]),
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Routine(True, True, "2b", "spr", T, [S,D,H], ["n"], ["layout","triangle"], ["x"], ["ap"], ["alpha"], "", "Symmetric packed rank-1 matrix update", "Same operation as xSPR, but matrix _A_ is a symmetric packed matrix instead and represented as _AP_.", []),
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Routine(True, True, "2b", "syr2", T, [S,D,H], ["n"], ["layout","triangle"], ["x","y"], ["a"], ["alpha"], "", "Symmetric rank-2 matrix update", "Same operation as xHER2, but matrix _A_ is a symmetric matrix instead.", [ald_n]),
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Routine(True, True, "2b", "spr2", T, [S,D,H], ["n"], ["layout","triangle"], ["x","y"], ["ap"], ["alpha"], "", "Symmetric packed rank-2 matrix update", "Same operation as xSPR2, but matrix _A_ is a symmetric packed matrix instead and represented as _AP_.", []),
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],
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[ # Level 3: matrix-matrix
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Routine(True, True, "3", "gemm", T, [S,D,C,Z,H], ["m","n","k"], ["layout","a_transpose","b_transpose"], ["a","b"], ["c"], ["alpha","beta"], "", "General matrix-matrix multiplication", "Performs the matrix product _C = alpha * A * B + beta * C_, in which _A_ (_m_ by _k_) and _B_ (_k_ by _n_) are two general rectangular input matrices, _C_ (_m_ by _n_) is the matrix to be updated, and _alpha_ and _beta_ are scalar values. The matrices _A_ and/or _B_ can optionally be transposed before performing the operation.", [ald_transa_m_k, bld_transb_k_n, cld_m]),
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Routine(True, True, "3", "symm", T, [S,D,C,Z,H], ["m","n"], ["layout","side","triangle"], ["a","b"], ["c"], ["alpha","beta"], "", "Symmetric matrix-matrix multiplication", "Same operation as xGEMM, but _A_ is symmetric instead. In case of `side == kLeft`, _A_ is a symmetric _m_ by _m_ matrix and _C = alpha * A * B + beta * C_ is performed. Otherwise, in case of `side == kRight`, _A_ is a symmtric _n_ by _n_ matrix and _C = alpha * B * A + beta * C_ is performed.", [ald_side_m_n, bld_m, cld_m]),
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Routine(True, True, "3", "hemm", T, [C,Z], ["m","n"], ["layout","side","triangle"], ["a","b"], ["c"], ["alpha","beta"], "", "Hermitian matrix-matrix multiplication", "Same operation as xSYMM, but _A_ is an Hermitian matrix instead.", [ald_side_m_n, bld_m, cld_m]),
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Routine(True, True, "3", "syrk", T, [S,D,C,Z,H], ["n","k"], ["layout","triangle","a_transpose"], ["a"], ["c"], ["alpha","beta"], "", "Rank-K update of a symmetric matrix", "Performs the matrix product _C = alpha * A * A^T + beta * C_ or _C = alpha * A^T * A + beta * C_, in which _A_ is a general matrix and _A^T_ is its transpose, _C_ (_n_ by _n_) is the symmetric matrix to be updated, and _alpha_ and _beta_ are scalar values.", [ald_trans_n_k, cld_m]),
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Routine(True, True, "3", "herk", Tc, [Css,Zdd], ["n","k"], ["layout","triangle","a_transpose"], ["a"], ["c"], ["alpha","beta"], "", "Rank-K update of a hermitian matrix", "Same operation as xSYRK, but _C_ is an Hermitian matrix instead.", [ald_trans_n_k, cld_m]),
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Routine(True, True, "3", "syr2k", T, [S,D,C,Z,H], ["n","k"], ["layout","triangle","ab_transpose"], ["a","b"], ["c"], ["alpha","beta"], "", "Rank-2K update of a symmetric matrix", "Performs the matrix product _C = alpha * A * B^T + alpha * B * A^T + beta * C_ or _C = alpha * A^T * B + alpha * B^T * A + beta * C_, in which _A_ and _B_ are general matrices and _A^T_ and _B^T_ are their transposed versions, _C_ (_n_ by _n_) is the symmetric matrix to be updated, and _alpha_ and _beta_ are scalar values.", [ald_trans_n_k, bld_trans_n_k, cld_n]),
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Routine(True, True, "3", "her2k", TU, [Ccs,Zzd], ["n","k"], ["layout","triangle","ab_transpose"], ["a","b"], ["c"], ["alpha","beta"], "", "Rank-2K update of a hermitian matrix", "Same operation as xSYR2K, but _C_ is an Hermitian matrix instead.", [ald_trans_n_k, bld_trans_n_k, cld_n]),
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Routine(True, True, "3", "trmm", T, [S,D,C,Z,H], ["m","n"], ["layout","side","triangle","a_transpose","diagonal"], ["a"], ["b"], ["alpha"], "", "Triangular matrix-matrix multiplication", "Performs the matrix product _B = alpha * A * B_ or _B = alpha * B * A_, in which _A_ is a unit or non-unit triangular matrix, _B_ (_m_ by _n_) is the general matrix to be updated, and _alpha_ is a scalar value.", [ald_side_m_n, bld_m]),
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Routine(False, True, "3", "trsm", T, [S,D,C,Z,H], ["m","n"], ["layout","side","triangle","a_transpose","diagonal"], ["a"], ["b"], ["alpha"], "", "Solves a triangular system of equations", "", []),
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],
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[ # Level X: extra routines (not part of BLAS)
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Routine(True, True, "x", "omatcopy", T, [S,D,C,Z,H], ["m","n"], ["layout","a_transpose"], ["a"], ["b"], ["alpha"], "", "Scaling and out-place transpose/copy (non-BLAS function)", "Performs scaling and out-of-place transposition/copying of matrices according to _B = alpha*op(A)_, in which _A_ is an input matrix (_m_ rows by _n_ columns), _B_ an output matrix, and _alpha_ a scalar value. The operation _op_ can be a normal matrix copy, a transposition or a conjugate transposition.", [ald_m, bld_n]),
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]]
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def main(argv):
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# Parses the command-line arguments
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parser = argparse.ArgumentParser()
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parser.add_argument("clblast_root", help="Root of the CLBlast sources")
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parser.add_argument("-v", "--verbose", action="store_true", help="Increase verbosity of the script")
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cl_args = parser.parse_args(argv)
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library_root = cl_args.clblast_root
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# Checks whether the command-line arguments are valid; exists otherwise
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for f in FILES:
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if not os.path.isfile(library_root + f):
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print("[ERROR] The path '" + library_root + "' does not point to the root of the CLBlast library")
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sys.exit()
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# Iterates over all regular files to output
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for i in range(0, len(FILES)):
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# Stores the header and the footer of the original file
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with open(library_root + FILES[i]) as f:
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original = f.readlines()
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file_header = original[:HEADER_LINES[i]]
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file_footer = original[-FOOTER_LINES[i]:]
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# Re-writes the body of the file
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with open(library_root + FILES[i], "w") as f:
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body = ""
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levels = [1, 2, 3] if (i == 4 or i == 5) else [1, 2, 3, 4]
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for level in levels:
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body += cpp.LEVEL_SEPARATORS[level - 1] + "\n"
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for routine in ROUTINES[level - 1]:
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if i == 0:
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body += cpp.clblast_h(routine)
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if i == 1:
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body += cpp.clblast_cc(routine)
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if i == 2:
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body += cpp.clblast_c_h(routine)
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if i == 3:
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body += cpp.clblast_c_cc(routine)
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if i == 4:
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body += cpp.wrapper_clblas(routine)
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if i == 5:
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body += cpp.wrapper_cblas(routine)
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f.write("".join(file_header))
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f.write(body)
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f.write("".join(file_footer))
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# Outputs all the test implementations
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for level in [1, 2, 3, 4]:
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for routine in ROUTINES[level - 1]:
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if routine.has_tests:
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level_string = cpp.LEVEL_NAMES[level - 1]
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routine_suffix = "level" + level_string + "/x" + routine.name + ".cpp"
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# Correctness tests
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filename = library_root + "/test/correctness/routines/" + routine_suffix
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with open(filename, "w") as f:
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f.write(cpp.HEADER + "\n")
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f.write(cpp.correctness_test(routine, level_string))
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f.write(cpp.FOOTER)
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# Performance tests
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filename = library_root + "/test/performance/routines/" + routine_suffix
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with open(filename, "w") as f:
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f.write(cpp.HEADER + "\n")
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f.write(cpp.performance_test(routine, level_string))
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f.write(cpp.FOOTER)
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# Outputs the API documentation
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filename = cl_args.clblast_root + "/doc/clblast.md"
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with open(filename, "w") as f:
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# Outputs the header
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doc_header = doc.header()
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f.write(doc_header)
|
|
|
|
# Generates the documentation for each routine
|
|
for level in [1, 2, 3, 4]:
|
|
for routine in ROUTINES[level - 1]:
|
|
if routine.implemented:
|
|
doc_routine = doc.generate(routine)
|
|
f.write(doc_routine)
|
|
|
|
if __name__ == '__main__':
|
|
main(sys.argv[1:])
|