3264360e1c1a0c1674ad20803c503e419ef60c09
[riscv-tests.git] / mt / af_matmul / bestattemptthusfar2.c
1 //**************************************************************************
2 // Multi-threaded Matrix Multiply benchmark
3 //--------------------------------------------------------------------------
4 // TA : Christopher Celio
5 // Student:
6 //
7 //
8 // This benchmark multiplies two 2-D arrays together and writes the results to
9 // a third vector. The input data (and reference data) should be generated
10 // using the matmul_gendata.pl perl script and dumped to a file named
11 // dataset.h.
12
13
14 // print out arrays, etc.
15 //#define DEBUG
16
17 //--------------------------------------------------------------------------
18 // Includes
19
20 #include <string.h>
21 #include <stdlib.h>
22 #include <stdio.h>
23
24
25 //--------------------------------------------------------------------------
26 // Input/Reference Data
27
28 typedef float data_t;
29 #include "dataset.h"
30
31
32 //--------------------------------------------------------------------------
33 // Basic Utilities and Multi-thread Support
34
35 __thread unsigned long coreid;
36 unsigned long ncores;
37
38 #include "util.h"
39
40 #define stringify_1(s) #s
41 #define stringify(s) stringify_1(s)
42 #define stats(code) do { \
43 unsigned long _c = -rdcycle(), _i = -rdinstret(); \
44 code; \
45 _c += rdcycle(), _i += rdinstret(); \
46 if (coreid == 0) \
47 printf("%s: %ld cycles, %ld.%ld cycles/iter, %ld.%ld CPI\n", \
48 stringify(code), _c, _c/DIM_SIZE/DIM_SIZE/DIM_SIZE, 10*_c/DIM_SIZE/DIM_SIZE/DIM_SIZE%10, _c/_i, 10*_c/_i%10); \
49 } while(0)
50
51
52 //--------------------------------------------------------------------------
53 // Helper functions
54
55 void printArrayMT( char name[], int n, data_t arr[] )
56 {
57 int i;
58 if (coreid != 0)
59 return;
60
61 printf( " %10s :", name );
62 for ( i = 0; i < n; i++ )
63 printf( " %3ld ", (long) arr[i] );
64 printf( "\n" );
65 }
66
67 void __attribute__((noinline)) verifyMT(size_t n, const data_t* test, const data_t* correct)
68 {
69 if (coreid != 0)
70 return;
71
72 size_t i;
73 for (i = 0; i < n; i++)
74 {
75 if (test[i] != correct[i])
76 {
77 printf("FAILED test[%d]= %3ld, correct[%d]= %3ld\n",
78 i, (long)test[i], i, (long)correct[i]);
79 exit(-1);
80 }
81 }
82
83 return;
84 }
85
86 data_t mult(data_t x, data_t y)
87 { data_t result = 0;
88 size_t i;
89 for (i=0; i < x; i++) {
90 result += y;
91 }
92 return result;
93 }
94 //--------------------------------------------------------------------------
95 // matmul function
96
97 // single-thread, naive version
98 void __attribute__((noinline)) matmul_naive(const int lda, const data_t A[], const data_t B[], data_t C[] )
99 {
100 int i, j, k;
101
102 if (coreid > 0)
103 return;
104
105 for ( i = 0; i < lda; i++ )
106 for ( j = 0; j < lda; j++ )
107 {
108 for ( k = 0; k < lda; k++ )
109 {
110 C[i + j*lda] += A[j*lda + k] * B[k*lda + i];
111 }
112 }
113
114 }
115
116
117 void __attribute__((noinline)) matmul(const int lda, const data_t A[], const data_t B[], data_t C[] )
118 {
119
120 size_t i, j, k, l;
121 int row,row2, column, column2, column3, column4, column5, column6, column7, column8;
122 data_t element, element2, element3, element4, element5, element6, element7, element8;
123 data_t B1, B2, B3, B4;
124 data_t temp_mat[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
125 data_t temp_mat2[32]={0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
126 int local_lda = lda;
127 //for (i=coreid*max_dim/ncores; i<(max_dim/ncores+coreid*max_dim/ncores); i+=8){
128 for (l=coreid*local_lda/ncores; l<local_lda*(1+coreid)/ncores; l+=2){
129 row=l*32;
130 row2=(l+1)*32;
131 //element = A[row];
132 //element5 = A[row2];
133 for (i=0; i<local_lda; i+=4){
134 element = A[row+i];
135 element2 = A[row+i+1];
136 element3 = A[row+i+2];
137 element4 = A[row+i+3];
138
139 element5 = A[row2+i];
140 element6 = A[row2+i+1];
141 element7 = A[row2+i+2];
142 element8 = A[row2+i+3];
143
144 column=i*local_lda;
145 column2=(i+1)*local_lda;
146 column3=(i+2)*local_lda;
147 column4=(i+3)*local_lda;
148
149 B1 = B[column];
150 B2 = B[column2];
151 B3 = B[column3];
152 B4 = B[column4];
153
154 for (j=0; j<lda; j+=4){
155 temp_mat[j]+=element*B1+element2*B2+element3*B3+element4*B4;
156 temp_mat[j+1]+=element*B[column+j+1]+element2*B[column2+j+1]+element3*B[column3+j+1]+element4*B[column4+j+1];
157 temp_mat[j+2]+=element*B[column+j+2]+element2*B[column2+j+2]+element3*B[column3+j+2]+element4*B[column4+j+2];
158 temp_mat[j+3]+=element*B[column+j+3]+element2*B[column2+j+3]+element3*B[column3+j+3]+element4*B[column4+j+3];
159
160 temp_mat2[j]+=element5*B1+element6*B2+element7*B3+element8*B4;
161 temp_mat2[j+1]+=element5*B[column+j+1]+element6*B[column2+j+1]+element7*B[column3+j+1]+element8*B[column4+j+1];
162 temp_mat2[j+2]+=element5*B[column+j+2]+element6*B[column2+j+2]+element7*B[column3+j+2]+element8*B[column4+j+2];
163 temp_mat2[j+3]+=element5*B[column+j+3]+element6*B[column2+j+3]+element7*B[column3+j+3]+element8*B[column4+j+3];
164
165 B1 = B[column+j+4];
166 B2 = B[column2+j+4];
167 B3 = B[column3+j+4];
168 B4 = B[column4+j+4];
169
170 }
171 //element = A[row+i+4];
172 //element5 = A[row2+i+4];
173 }
174
175 for(k=0; k<local_lda; k++){
176 C[row+k]=temp_mat[k];
177 temp_mat[k]=0;
178 C[row2+k]=temp_mat2[k];
179 temp_mat2[k]=0;
180
181 }
182
183
184 }
185
186 // ***************************** //
187 // **** ADD YOUR CODE HERE ***** //
188 // ***************************** //
189 //
190 // feel free to make a separate function for MI and MSI versions.
191
192 }
193 //--------------------------------------------------------------------------
194 // Main
195 //
196 // all threads start executing thread_entry(). Use their "coreid" to
197 // differentiate between threads (each thread is running on a separate core).
198
199 void thread_entry(int cid, int nc)
200 {
201 coreid = cid;
202 ncores = nc;
203
204 // static allocates data in the binary, which is visible to both threads
205 static data_t results_data[ARRAY_SIZE];
206
207
208 // Execute the provided, naive matmul
209 barrier(nc);
210 stats(matmul_naive(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));
211
212
213 // verify
214 verifyMT(ARRAY_SIZE, results_data, verify_data);
215
216 // clear results from the first trial
217 size_t i;
218 if (coreid == 0)
219 for (i=0; i < ARRAY_SIZE; i++)
220 results_data[i] = 0;
221 barrier(nc);
222
223
224 // Execute your faster matmul
225 barrier(nc);
226 stats(matmul(DIM_SIZE, input1_data, input2_data, results_data); barrier(nc));
227
228 #ifdef DEBUG
229 printArrayMT("results:", ARRAY_SIZE, results_data);
230 printArrayMT("verify :", ARRAY_SIZE, verify_data);
231 #endif
232
233 // verify
234 verifyMT(ARRAY_SIZE, results_data, verify_data);
235 barrier(nc);
236
237 exit(0);
238 }