From: Andrey Miroshnikov Date: Tue, 17 Oct 2023 13:06:31 +0000 (+0000) Subject: Added pure python mat multiply (outer and inner product versions). Made result printi... X-Git-Url: https://git.libre-soc.org/?a=commitdiff_plain;h=1270da46c396f91bc1a65c85b06896b9b378c2f4;p=openpower-isa.git Added pure python mat multiply (outer and inner product versions). Made result printing parametrisable. --- diff --git a/src/openpower/decoder/isa/test_caller_svp64_matrix.py b/src/openpower/decoder/isa/test_caller_svp64_matrix.py index 3a413fef..f25d3c69 100644 --- a/src/openpower/decoder/isa/test_caller_svp64_matrix.py +++ b/src/openpower/decoder/isa/test_caller_svp64_matrix.py @@ -9,15 +9,41 @@ from openpower.decoder.selectable_int import SelectableInt from openpower.simulator.program import Program from openpower.insndb.asm import SVP64Asm +def setup_result_matrix(rows, cols): + result = [] + for i in range(0, rows): + result.append([]) + for k in range(0, cols): + result[-1].append(0) + return result + +# Outer product - normal method learned at school +def matmult_outer(a,b): + # Result matrix has same number of rows as matrix a + # and same number of columns as matrix b + result = setup_result_matrix(len(a), len(b[0])) + + for i in range(len(a)): # Number of rows in matrix a + for k in range(len(b[0])): # Number of columns in matrix b + # Number of columns in matrix a or rows in mat b + for j in range(0, len(a[0])): + result[i][k] += a[i][j] * b[j][k] + + return result + +# Inner product - slight re-arrangement to reduce stalling +# on cpu pipeline +def matmult_inner(a,b): + result = setup_result_matrix(len(a), len(b[0])) + + for i in range(len(a)): # Number of rows in matrix a + # Number of columns in matrix a or rows in mat b + for j in range(0, len(a[0])): + for k in range(len(b[0])): # Number of columns in matrix b + result[i][k] += a[i][j] * b[j][k] + + return result -# Pure Python implementation of matrix multiply -# Example values -# x = [[1,2,3],[4,5,6],[7,8,9],[10,11,12]] -# y = [[1,2],[1,2],[3,4]] -def matmult(a, b): - zip_b = list(zip(*b)) # transpose b matrix - return [[sum(ele_a*ele_b for ele_a, ele_b in zip(row_a, col_b)) - for col_b in zip_b] for row_a in a] class DecoderTestCase(FHDLTestCase): @@ -54,9 +80,14 @@ class DecoderTestCase(FHDLTestCase): X = X1 Y = Y1 - expected = matmult(X, Y) - print("expected-matrix:") + expected = matmult_outer(X, Y) + expected2 = matmult_inner(X, Y) + expected = flatten(expected) + expected2 = flatten(expected2) + print("expected-matrix (outer):") print(expected) + print("expected-matrix (inner):") + print(expected2) xf = reduce(operator.add, X) yf = reduce(operator.add, Y) @@ -86,9 +117,10 @@ class DecoderTestCase(FHDLTestCase): print("spr svshape2", sim.spr['SVSHAPE2']) print("spr svshape3", sim.spr['SVSHAPE3']) results = [] - for i in range(4): + total = len(X)*len(Y[0]) + for i in range(total): results.append(sim.gpr(i).asint()) - for i in range(4): + for i in range(total): print("maddld-matrix i", i, results[i]) # confirm that the results are as expected self.assertEqual(results, expected)