360 lines
9.4 KiB
C
360 lines
9.4 KiB
C
/*
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Copyright 2018 Embedded Microprocessor Benchmark Consortium (EEMBC)
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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Original Author: Shay Gal-on
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*/
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#include "coremark.h"
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/*
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Topic: Description
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Matrix manipulation benchmark
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This very simple algorithm forms the basis of many more complex
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algorithms.
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The tight inner loop is the focus of many optimizations (compiler as
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well as hardware based) and is thus relevant for embedded processing.
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The total available data space will be divided to 3 parts:
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NxN Matrix A - initialized with small values (upper 3/4 of the bits all
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zero). NxN Matrix B - initialized with medium values (upper half of the bits all
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zero). NxN Matrix C - used for the result.
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The actual values for A and B must be derived based on input that is not
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available at compile time.
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*/
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ee_s16 matrix_test(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B, MATDAT val);
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ee_s16 matrix_sum(ee_u32 N, MATRES *C, MATDAT clipval);
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void matrix_mul_const(ee_u32 N, MATRES *C, MATDAT *A, MATDAT val);
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void matrix_mul_vect(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B);
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void matrix_mul_matrix(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B);
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void matrix_mul_matrix_bitextract(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B);
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void matrix_add_const(ee_u32 N, MATDAT *A, MATDAT val);
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#define matrix_test_next(x) (x + 1)
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#define matrix_clip(x, y) ((y) ? (x)&0x0ff : (x)&0x0ffff)
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#define matrix_big(x) (0xf000 | (x))
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#define bit_extract(x, from, to) (((x) >> (from)) & (~(0xffffffff << (to))))
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#if CORE_DEBUG
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void
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printmat(MATDAT *A, ee_u32 N, char *name)
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{
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ee_u32 i, j;
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ee_printf("Matrix %s [%dx%d]:\n", name, N, N);
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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if (j != 0)
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ee_printf(",");
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ee_printf("%d", A[i * N + j]);
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}
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ee_printf("\n");
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}
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}
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void
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printmatC(MATRES *C, ee_u32 N, char *name)
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{
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ee_u32 i, j;
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ee_printf("Matrix %s [%dx%d]:\n", name, N, N);
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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if (j != 0)
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ee_printf(",");
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ee_printf("%d", C[i * N + j]);
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}
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ee_printf("\n");
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}
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}
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#endif
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/* Function: core_bench_matrix
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Benchmark function
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Iterate <matrix_test> N times,
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changing the matrix values slightly by a constant amount each time.
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*/
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ee_u16
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core_bench_matrix(mat_params *p, ee_s16 seed, ee_u16 crc)
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{
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ee_u32 N = p->N;
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MATRES *C = p->C;
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MATDAT *A = p->A;
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MATDAT *B = p->B;
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MATDAT val = (MATDAT)seed;
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crc = crc16(matrix_test(N, C, A, B, val), crc);
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return crc;
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}
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/* Function: matrix_test
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Perform matrix manipulation.
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Parameters:
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N - Dimensions of the matrix.
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C - memory for result matrix.
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A - input matrix
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B - operator matrix (not changed during operations)
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Returns:
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A CRC value that captures all results calculated in the function.
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In particular, crc of the value calculated on the result matrix
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after each step by <matrix_sum>.
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Operation:
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1 - Add a constant value to all elements of a matrix.
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2 - Multiply a matrix by a constant.
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3 - Multiply a matrix by a vector.
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4 - Multiply a matrix by a matrix.
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5 - Add a constant value to all elements of a matrix.
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After the last step, matrix A is back to original contents.
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*/
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ee_s16
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matrix_test(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B, MATDAT val)
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{
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ee_u16 crc = 0;
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MATDAT clipval = matrix_big(val);
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matrix_add_const(N, A, val); /* make sure data changes */
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#if CORE_DEBUG
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printmat(A, N, "matrix_add_const");
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#endif
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matrix_mul_const(N, C, A, val);
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crc = crc16(matrix_sum(N, C, clipval), crc);
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#if CORE_DEBUG
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printmatC(C, N, "matrix_mul_const");
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#endif
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matrix_mul_vect(N, C, A, B);
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crc = crc16(matrix_sum(N, C, clipval), crc);
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#if CORE_DEBUG
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printmatC(C, N, "matrix_mul_vect");
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#endif
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matrix_mul_matrix(N, C, A, B);
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crc = crc16(matrix_sum(N, C, clipval), crc);
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#if CORE_DEBUG
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printmatC(C, N, "matrix_mul_matrix");
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#endif
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matrix_mul_matrix_bitextract(N, C, A, B);
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crc = crc16(matrix_sum(N, C, clipval), crc);
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#if CORE_DEBUG
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printmatC(C, N, "matrix_mul_matrix_bitextract");
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#endif
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matrix_add_const(N, A, -val); /* return matrix to initial value */
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return crc;
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}
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/* Function : matrix_init
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Initialize the memory block for matrix benchmarking.
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Parameters:
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blksize - Size of memory to be initialized.
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memblk - Pointer to memory block.
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seed - Actual values chosen depend on the seed parameter.
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p - pointers to <mat_params> containing initialized matrixes.
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Returns:
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Matrix dimensions.
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Note:
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The seed parameter MUST be supplied from a source that cannot be
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determined at compile time
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*/
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ee_u32
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core_init_matrix(ee_u32 blksize, void *memblk, ee_s32 seed, mat_params *p)
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{
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ee_u32 N = 0;
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MATDAT *A;
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MATDAT *B;
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ee_s32 order = 1;
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MATDAT val;
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ee_u32 i = 0, j = 0;
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if (seed == 0)
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seed = 1;
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while (j < blksize)
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{
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i++;
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j = i * i * 2 * 4;
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}
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N = i - 1;
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A = (MATDAT *)align_mem(memblk);
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B = A + N * N;
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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seed = ((order * seed) % 65536);
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val = (seed + order);
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val = matrix_clip(val, 0);
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B[i * N + j] = val;
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val = (val + order);
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val = matrix_clip(val, 1);
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A[i * N + j] = val;
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order++;
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}
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}
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p->A = A;
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p->B = B;
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p->C = (MATRES *)align_mem(B + N * N);
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p->N = N;
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#if CORE_DEBUG
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printmat(A, N, "A");
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printmat(B, N, "B");
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#endif
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return N;
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}
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/* Function: matrix_sum
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Calculate a function that depends on the values of elements in the
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matrix.
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For each element, accumulate into a temporary variable.
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As long as this value is under the parameter clipval,
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add 1 to the result if the element is bigger then the previous.
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Otherwise, reset the accumulator and add 10 to the result.
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*/
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ee_s16
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matrix_sum(ee_u32 N, MATRES *C, MATDAT clipval)
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{
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MATRES tmp = 0, prev = 0, cur = 0;
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ee_s16 ret = 0;
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ee_u32 i, j;
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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cur = C[i * N + j];
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tmp += cur;
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if (tmp > clipval)
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{
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ret += 10;
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tmp = 0;
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}
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else
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{
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ret += (cur > prev) ? 1 : 0;
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}
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prev = cur;
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}
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}
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return ret;
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}
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/* Function: matrix_mul_const
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Multiply a matrix by a constant.
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This could be used as a scaler for instance.
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*/
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void
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matrix_mul_const(ee_u32 N, MATRES *C, MATDAT *A, MATDAT val)
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{
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ee_u32 i, j;
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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C[i * N + j] = (MATRES)A[i * N + j] * (MATRES)val;
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}
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}
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}
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/* Function: matrix_add_const
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Add a constant value to all elements of a matrix.
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*/
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void
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matrix_add_const(ee_u32 N, MATDAT *A, MATDAT val)
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{
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ee_u32 i, j;
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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A[i * N + j] += val;
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}
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}
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}
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/* Function: matrix_mul_vect
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Multiply a matrix by a vector.
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This is common in many simple filters (e.g. fir where a vector of
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coefficients is applied to the matrix.)
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*/
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void
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matrix_mul_vect(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B)
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{
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ee_u32 i, j;
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for (i = 0; i < N; i++)
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{
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C[i] = 0;
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for (j = 0; j < N; j++)
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{
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C[i] += (MATRES)A[i * N + j] * (MATRES)B[j];
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}
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}
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}
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/* Function: matrix_mul_matrix
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Multiply a matrix by a matrix.
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Basic code is used in many algorithms, mostly with minor changes such as
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scaling.
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*/
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void
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matrix_mul_matrix(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B)
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{
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ee_u32 i, j, k;
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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C[i * N + j] = 0;
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for (k = 0; k < N; k++)
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{
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C[i * N + j] += (MATRES)A[i * N + k] * (MATRES)B[k * N + j];
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}
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}
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}
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}
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/* Function: matrix_mul_matrix_bitextract
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Multiply a matrix by a matrix, and extract some bits from the result.
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Basic code is used in many algorithms, mostly with minor changes such as
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scaling.
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*/
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void
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matrix_mul_matrix_bitextract(ee_u32 N, MATRES *C, MATDAT *A, MATDAT *B)
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{
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ee_u32 i, j, k;
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for (i = 0; i < N; i++)
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{
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for (j = 0; j < N; j++)
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{
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C[i * N + j] = 0;
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for (k = 0; k < N; k++)
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{
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MATRES tmp = (MATRES)A[i * N + k] * (MATRES)B[k * N + j];
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C[i * N + j] += bit_extract(tmp, 2, 4) * bit_extract(tmp, 5, 7);
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}
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}
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}
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}
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