From 7356cec4b5b80e9ce914625d39be0ac6cc1b4d86 Mon Sep 17 00:00:00 2001
From: xiyehu2 <35537592+xiyehu2@users.noreply.github.com>
Date: Wed, 7 Dec 2022 15:39:00 -0600
Subject: [PATCH] More stuff to lookat
---
Python/benchmarking.py | 41 ++++++++++++++++++++++++++---------------
1 file changed, 26 insertions(+), 15 deletions(-)
diff --git a/Python/benchmarking.py b/Python/benchmarking.py
index 0e84932..1dc36e4 100644
--- a/Python/benchmarking.py
+++ b/Python/benchmarking.py
@@ -6,8 +6,8 @@ import cupy as cp
def test(f_idx, t_idx):
- paths, off = get_rearrange_paths(f_idx, t_idx)
- create_moving_array_reduced(_sig, _table_cp, paths, off)
+ create_moving_array_reduced(_table_cp, _sig, f_idx, t_idx)
+ return cp.asnumpy(_sig)
def count(paths, path_table, off):
@@ -24,8 +24,8 @@ def count(paths, path_table, off):
return counter
-data = np.load("data/table-half_31.npz", allow_pickle=True)
-table = data['path_table'].item()
+data = np.load("table/table-half_31_120722.npz", allow_pickle=True)
+table = data['table'].item()
twzr = data['wfm'].item()
static_sig = data['static_sig']
target = data['target']
@@ -38,14 +38,18 @@ for key in table:
_table_cp[key] = cp.array(table[key])
n_repeat = 500
-_sig = cp.array(static_sig)
-times = np.zeros((nt+1,2))
-filling_ratio = np.zeros((nt+1,2))
-n_move = np.zeros((nt+1,n_repeat))
+total_t = np.zeros((nt+1, 2))
+gpu_t = np.zeros((nt+1, 2))
+cpu_t = np.zeros((nt+1, 2))
+filling_ratio = np.zeros((nt+1, 2))
+n_move = np.zeros((nt+1, 2))
for i in range(nt+1):
+ _sig = cp.array(static_sig)
f_prob = i/nt
- calc_t = np.zeros(n_repeat)
+ t_t = np.zeros(n_repeat)
+ g_t = np.zeros(n_repeat)
+ c_t = np.zeros(n_repeat)
ratio = np.zeros(n_repeat)
nm = np.zeros(n_repeat)
print(i, f_prob)
@@ -63,24 +67,31 @@ for i in range(nt+1):
)
# stuff to save
ratio[j] = f_idx.size / nt
- calc_t[j] = b.gpu_times + b.cpu_times
+ g_t[j] = b.gpu_times
+ c_t[j] = b.cpu_times
+ t_t[j] = b.gpu_times + b.cpu_times
paths, off = get_rearrange_paths(f_idx, t_idx)
nm[j] = count(paths, _table_cp, off)
# n_move[i,0] = np.mean(nm)
# n_move[i,1] = np.var(nm)
- n_move[i] = nm
- times[i,0] = np.mean(calc_t)
- times[i,1] = np.var(calc_t)
+ n_move[i,0] = np.mean(nm)
+ n_move[i,1] = np.var(nm)
+ gpu_t[i,0] = np.mean(g_t)
+ gpu_t[i,1] = np.var(g_t)
+ cpu_t[i,0] = np.mean(c_t)
+ cpu_t[i,1] = np.var(c_t)
+ total_t[i,0] = np.mean(t_t)
+ total_t[i,1] = np.var(t_t)
filling_ratio[i,0] = np.mean(ratio)
filling_ratio[i,1] = np.var(ratio)
np.savez(
- f"data/reduced-benchmark_{nt}-half.npz",
+ f"data/120722_benchmark_{nt}-half_wfm-only.npz",
wfm=twzr,
target=target,
filling_ratio=filling_ratio,
- times=times,
+ times=[gpu_t, cpu_t, total_t],
n_move=n_move
)
--
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