numeric-linalg

Educational material on the SciPy implementation of numerical linear algebra algorithms

Commit
45fe249a132b03b316a5ed97805749f53d28924c
Parent
f529d36ef76eacfbad8d463b547b3b8a8db9be7e
Author
Pablo <pablo-pie@riseup.net>
Date

Formatted the comments

Diffstats

2 files changed, 10 insertions, 10 deletions

Status Name Changes Insertions Deletions
Modified getrf/benchmarks/src/main.c 2 files changed 9 9
Modified getrf/benchmarks/src/perf.h 2 files changed 1 1
diff --git a/getrf/benchmarks/src/main.c b/getrf/benchmarks/src/main.c
@@ -32,7 +32,7 @@ ProgressBar progress = {
 typedef struct {
   double       *ref_data;
 
-  // Input parameters for dgetrf
+  // input parameters for dgetrf
   double       *data;
   int32_t      ipiv[MAX_N];
   int          n, m, lda, info;
@@ -54,9 +54,9 @@ extern void dgetrf2_(int *m, int *n, double *A, int *lda, int *ipiv, int *info);
 
 PerfResult thread_run_benchmark(Thread *thread, size_t n)
 {
-  // Reinitializes the values in the .data array: this avoids progressively
-  // moving larger values to the beginning of the array, which would decrise
-  // decrease the number of row interchanges required for computations
+  // reinitializes the values in the .data array: this avoids progressively
+  // moving larger values to the beginning of the array, which would decrease
+  // the number of row interchanges required for computations
   memcpy(thread->data, thread->ref_data, sizeof(double)*n*n);
   thread->n = n; thread->m = n; thread->lda = n;
 
@@ -70,7 +70,7 @@ void *thread_benchmark(void *arg)
 {
   Thread *thread = (Thread*) arg;
 
-  // We need to lock the running thread to some CPU so that we can mask
+  // we need to lock the running thread to some CPU so that we can mask
   // perf_event_open with this specific CPU
   cpu_set_t set;
   CPU_ZERO(&set);
@@ -80,7 +80,7 @@ void *thread_benchmark(void *arg)
             thread->id);
   }
 
-  // Computations are distributed evenly across threads
+  // computations are distributed evenly across threads
   for (size_t n = 1 + thread->id*STEP; n < MAX_N; n += STEP*N_THREADS) {
     PerfResult result = thread_run_benchmark(thread, n);
     size_t i = (n - 1)/STEP;
@@ -102,7 +102,7 @@ Benchmarker benchmarker_new(double *ref_data)
 {
   Benchmarker bench = {0};
 
-  // This array will live for the entire duration of the program,
+  // this array will live for the entire duration of the program,
   // so we might as well leak it 🤡
   double *data = malloc(sizeof(double)*MAX_N*MAX_N*N_THREADS);
   if (data == NULL) {
@@ -167,7 +167,7 @@ int main(int argc, char **argv)
   // ========================================================================
   printf("INFO: Initializing random input data... ");
 
-  // This array will live for the entire duration of the program,
+  // this array will live for the entire duration of the program,
   // so we might as well leak it 🤡
   double *ref_data = malloc(sizeof(double)*MAX_N*MAX_N);
   if (ref_data == NULL) {
@@ -175,7 +175,7 @@ int main(int argc, char **argv)
     exit(EXIT_FAILURE);
   }
 
-  // Pseudorandom data given by the logistic map
+  // pseudorandom data given by the logistic map
   double acc = LOGISTICS_INITIAL_CONDITION;
   for (size_t i = 0; i < MAX_N*MAX_N; i++) {
     ref_data[i] = acc;
diff --git a/getrf/benchmarks/src/perf.h b/getrf/benchmarks/src/perf.h
@@ -15,7 +15,7 @@
 #include <assert.h>
 
 enum {
-  // Here we use L1-dcache-loads & L1-dcache-loads-misses instead of
+  // here we use L1-dcache-loads & L1-dcache-loads-misses instead of
   // cache-misses & cache-references because the L1 data cache is the only
   // CPU-specific cache accessible to perf: the LD cache is shared between
   // cores