Small coding style corrections

This commit is contained in:
doinachiroiu 2020-08-27 16:55:55 +00:00
parent 60b3b5057c
commit b2351ec639
2 changed files with 13 additions and 16 deletions

View File

@ -43,7 +43,7 @@ transformations and print the speed for each value and type of
transformation. More specifically, the input length is the target for
accuracy (named as `N`) and it stands for the number of data points from
the series that calculate the result of transformation. It is also
important to mention that the `cplx` variable stands for a boolean value
important to mention that the `complex` variable stands for a boolean value
that tells the type of transformation (0 for REAL and 1 for COMPLEX) and
it is taken into account while testing.
In the end, the performance of PFFFT library it is outlined by the output.

View File

@ -67,7 +67,7 @@ DEFINE_validator(output_format, &ValidateFlag);
double UclockSec() { return static_cast<double>(clock()) / CLOCKS_PER_SEC; }
void ShowOutput(const char* name, int n, int cplx, float flops, float t0,
void ShowOutput(const char* name, int n, int complex, float flops, float t0,
float t1, int max_iter) {
float mflops = flops / 1e6 / (t1 - t0 + 1e-16);
if (FLAGS_output_format) {
@ -78,7 +78,7 @@ void ShowOutput(const char* name, int n, int cplx, float flops, float t0,
} else {
if (flops != -1) {
printf("n=%5d, %s %16s : %6.0f MFlops [t=%6.0f ns, %d runs]\n", n,
(cplx ? "CPLX" : "REAL"), name, mflops,
(complex ? "CPLX" : "REAL"), name, mflops,
(t1 - t0) / 2 / max_iter * 1e9, max_iter);
}
}
@ -90,7 +90,6 @@ absl::Status PffftMain() {
SAPI_RETURN_IF_ERROR(sandbox.Init());
PffftApi api(&sandbox);
int cplx = 0;
// kTransformSizes is a vector keeping the values by which iterates n, its
// value representing the input length. More concrete, n is the number of data
@ -101,9 +100,9 @@ absl::Status PffftMain() {
64, 96, 128, 160, 192, 256, 384, 5 * 96, 512, 5 * 128,
3 * 256, 800, 1024, 2048, 2400, 4096, 8192, 9 * 1024, 16384, 32768};
do {
for (int complex : {0, 1}) {
for (int n : kTransformSizes) {
const int n_float = n * (cplx ? 2 : 1);
const int n_float = n * (complex ? 2 : 1);
int n_bytes = n_float * sizeof(float);
std::vector<float> work(2 * n_float + 15, 0.0);
@ -134,7 +133,7 @@ absl::Status PffftMain() {
int simd_size_iter = max_iter / 4;
if (simd_size_iter == 0) simd_size_iter = 1;
if (cplx) {
if (complex) {
api.cffti(n, work_array.PtrBoth()).IgnoreError();
} else {
api.rffti(n, work_array.PtrBoth()).IgnoreError();
@ -142,7 +141,7 @@ absl::Status PffftMain() {
t0 = UclockSec();
for (int iter = 0; iter < simd_size_iter; ++iter) {
if (cplx) {
if (complex) {
api.cfftf(n, x_array.PtrBoth(), work_array.PtrBoth()).IgnoreError();
api.cfftb(n, x_array.PtrBoth(), work_array.PtrBoth()).IgnoreError();
} else {
@ -153,14 +152,14 @@ absl::Status PffftMain() {
t1 = UclockSec();
flops = (simd_size_iter * 2) *
((cplx ? 5 : 2.5) * n * log((double)n) / M_LN2);
ShowOutput("FFTPack", n, cplx, flops, t0, t1, simd_size_iter);
((complex ? 5 : 2.5) * n * log((double)n) / M_LN2);
ShowOutput("FFTPack", n, complex, flops, t0, t1, simd_size_iter);
}
// PFFFT benchmark
{
sapi::StatusOr<PFFFT_Setup*> s =
api.pffft_new_setup(n, cplx ? PFFFT_COMPLEX : PFFFT_REAL);
api.pffft_new_setup(n, complex ? PFFFT_COMPLEX : PFFFT_REAL);
LOG(INFO) << "Setup status is: " << s.status().ToString();
@ -184,16 +183,14 @@ absl::Status PffftMain() {
t1 = UclockSec();
api.pffft_destroy_setup(&s_reg).IgnoreError();
flops = (max_iter * 2) * ((cplx ? 5 : 2.5) * static_cast<double>(n) *
flops = (max_iter * 2) * ((complex ? 5 : 2.5) * static_cast<double>(n) *
log((double)n) / M_LN2);
ShowOutput("PFFFT", n, cplx, flops, t0, t1, max_iter);
ShowOutput("PFFFT", n, complex, flops, t0, t1, max_iter);
LOG(INFO) << "n = " << n << " SUCCESSFULLY";
}
}
cplx = !cplx;
} while (cplx);
}
return absl::OkStatus();
}