Hi, I took a look at the GSoC 2017 ideas and I saw that one of the topics was the code generation. You said that there is work on updating the system ongoing. I'm really interested to know what this work is about.
I will try to explain why. I develop a Python package call pyLBM (https://www.math.u-psud.fr/pyLBM/) to use lattice Boltzmann methods. The idea is that a user specifies his symbolic scheme for LBM using sympy and then we generate the numerical code associated. In the master of pyLBM, we implement our own template to write cython and numpy versions. But, few weeks ago, I have decided to look at the code generation in sympy because we want to add other implementation like pythran or loopy easily and it is a lot of pain with our template. I think also that with sympy it could be easy to add some strategies during the code generation like cache blocking, SIMD, loop unrolling, ... The codeprinters in sympy are very useful and save a lot of time. On the other side, I had some difficulties with the original codegen to generate a numerical code so I have to rewrite it. For the moment, I have a cython version but it is very extensible. I will implement the numpy, pythran and loopy versions in few days. The current implementation of codegen support only MatrixSymbol, so I had to add Matrix expression. I also supposed that all expression must be an equality (for the moment). It was also difficult to write loop with only the Idx so I add a sympy expression called Loop to set a loop block in my codegen. I show you just two examples of the input and output. First example ========== Input: from pyLBM.generator import codegen from sympy import * M = Matrix([[1/4, 1/2, 0, 1/4], [1/4, 0, 1/2, -1/4], [1/4, -1/2, 0, 1/4], [1/4, 0, -1/2, -1/4]]) f = MatrixSymbol('f', 4, 1) m = MatrixSymbol('m', 4, 1) res = codegen(('m2f', Eq(f, M*m)), "cython", header=False) print(res[0][1] Output: def m2f(double[::1] f, double[::1] m): f[0] = 0.25*m[0] + 0.5*m[1] + 0.25*m[3] f[1] = 0.25*m[0] + 0.5*m[2] - 0.25*m[3] f[2] = 0.25*m[0] - 0.5*m[1] + 0.25*m[3] f[3] = 0.25*m[0] - 0.5*m[2] - 0.25*m[3] Second example ============ Input: from pyLBM.generator import codegen, Loop from sympy import * from sympy.abc import z n, m = symbols('n m', integer=True) A = IndexedBase('A', shape=(m, n, 4)) ff = IndexedBase('f', shape=(m, n, 4)) i = Idx('i', m) j = Idx('j', n) k = Idx('k', 4) m = MatrixSymbol('m', 4, 1) mnew = Matrix([A[i, j, kk] for kk in range(4)]) fnew = Matrix([ff[i, j, kk] for kk in range(4)]) eq = Matrix([[m[0]], [m[1]], [m[2]], [ 0.0]]) for ii in range(mnew.shape[0]): eq = eq.subs(m[ii], mnew[ii]) l2 = Loop('l2', k, Eq(z,k, evaluate=False)) l1 = Loop('l1', (i, j), [Eq(fnew, eq, evaluate=False), l2]) res = codegen(('test', l1), "CYTHON", header=False) print(res[0][1]) Output: def test(double[:, :, ::1] f, double[:, :, ::1] A, double z): cdef int j cdef int k cdef int i for i in range(0, m): for j in range(0, n): f[i, j, 0] = A[i, j, 0] f[i, j, 1] = A[i, j, 1] f[i, j, 2] = A[i, j, 2] f[i, j, 3] = 0.0 for k in range(0, 4): z = k -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sympy+unsubscr...@googlegroups.com. To post to this group, send email to sympy@googlegroups.com. Visit this group at https://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/91d462aa-0f40-441c-9667-df6f438383f1%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
