1 files changed, 6 insertions, 30 deletions
diff --git a/expt_0510.cu b/expt_0510.cu
index 82f2624..eca1b92 100644
--- a/expt_0510.cu
+++ b/expt_0510.cu
@@ -1,6 +1,7 @@
 // Experimental content: Test branch performance (optimized memory)
 #include "sortlib.cuh"
 
+#include "read_helper.h"
 #include <algorithm>
 #include <cassert>
 #include <cstdio>
@@ -167,34 +168,6 @@ unsigned long randomRow(unsigned long max_value_) {
   return dst(mt19937);
 }
 
-void readFile(char const *filename, long sample_length,
-              unsigned long &total_row,
-              unsigned long max_number = TEST_LENGTH) {
-  auto read_number = 0UL;
-  FILE *file = fopen(filename, "r");
-  assert(file);
-  for (long long i;
-       read_number < max_number && fscanf(file, "%lld ", &i) != EOF;
-       store_into_vector(i))
-    read_number++;
-
-  if (total_row > 0) {
-    read_number = randomRow(total_row - sample_length - max_number - 256);
-    total_row = read_number;
-    // fprintf(stderr, "Skip %lu\n", read_number);
-    for (long long i; read_number > 0 && fscanf(file, "%lld ", &i) != EOF;)
-      read_number--;
-  }
-
-  read_number = 0;
-
-  auto remain = sample_length + 256;
-  for (long long i; read_number < remain && fscanf(file, "%lld ", &i) != EOF;
-       store_into_vector(i))
-    read_number++;
-  fclose(file);
-}
-
 long pow_for_sample(long n) {
   auto x = 2;
   for (int i = 0; i < n; i++) {
@@ -225,10 +198,13 @@ int main(int argc, char const *argv[]) {
 
   // CustomSort::testSelf(sample_length);
 
-  readFile("normal_distribution.txt", sample_length, total_row, test_size);
+  ReadHelper readHelper("normal_distribution.txt", sample_length, test_size,
+                        total_row);
+  readHelper.readFile();
 
   printf("population: %zu, skip: %lu, test size: %zu, sample length: %zu | ",
-         population_vector.size(), total_row, test_size, sample_length);
+         population_vector.size(), readHelper.random_number, test_size,
+         sample_length);
 
   sample_vector = std::vector<key_type>(
       population_vector.begin(), population_vector.begin() + sample_length - 2);