From f3220fdfa35c7fbca62430707623be3c36487cf2 Mon Sep 17 00:00:00 2001
From: GuillaumeDIDIER <guillaume.didier95@hotmail.fr>
Date: Wed, 5 Aug 2020 11:11:49 +0200
Subject: [PATCH] Python script fixes
---
cache_utils/2T-opt-2020-07-31/analyse_csv.py | 24 +++++++++++++++++--
.../2T-opt-2020-07-31/analyse_medians.py | 6 +++++
requirements.txt | 5 ++++
3 files changed, 33 insertions(+), 2 deletions(-)
diff --git a/cache_utils/2T-opt-2020-07-31/analyse_csv.py b/cache_utils/2T-opt-2020-07-31/analyse_csv.py
index 6a3d70a..c9caf37 100644
--- a/cache_utils/2T-opt-2020-07-31/analyse_csv.py
+++ b/cache_utils/2T-opt-2020-07-31/analyse_csv.py
@@ -9,13 +9,29 @@ from functools import partial
import sys
+# For cyber cobay sanity check :
+from gmpy2 import popcount
+functions_i9_9900 = [
+ 0b1111111111010101110101010001000000,
+ 0b0110111110111010110001001000000000,
+ 0b1111111000011111110010110000000000]
+
+
+def complex_hash(addr):
+ r = 0
+ for f in reversed(functions_i9_9900):
+ r <<= 1
+ r |= (popcount(f & addr) & 1)
+ return r
+
+
def convert64(x):
return np.int64(int(x, base=16))
def convert8(x):
return np.int8(int(x, base=16))
-df = pd.read_csv(sys.argv[1] + "-result_lite.csv.bz2",
+df = pd.read_csv(sys.argv[1] + "-results_lite.csv.bz2",
dtype={
"main_core": np.int8,
"helper_core": np.int8,
@@ -59,6 +75,10 @@ sample_flush_columns = [
print(df.columns)
#df["Hash"] = df["Addr"].apply(lambda x: (x >> 15)&0x3)
+addresses = df["address"].unique()
+print(addresses)
+print(*[bin(a) for a in addresses], sep='\n')
+
print(df.head())
print(df["hash"].unique())
@@ -124,7 +144,7 @@ stats["clflush_shared_hit"] = hit_shared.values
stats.to_csv(sys.argv[1] + ".stats.csv", index=False)
-print(stats.to_string())
+#print(stats.to_string())
plt.show()
exit(0)
diff --git a/cache_utils/2T-opt-2020-07-31/analyse_medians.py b/cache_utils/2T-opt-2020-07-31/analyse_medians.py
index c846bc1..23ed107 100644
--- a/cache_utils/2T-opt-2020-07-31/analyse_medians.py
+++ b/cache_utils/2T-opt-2020-07-31/analyse_medians.py
@@ -75,6 +75,12 @@ graph_upper_miss = int(((max_time_miss + 9) // 10) * 10)
print("Graphing from {} to {}".format(graph_lower_miss, graph_upper_miss))
+g_ = sns.FacetGrid(stats, col="main_core_fixed", row="slice_group")
+
+g_.map(sns.distplot, 'clflush_miss_n', bins=range(graph_lower_miss, graph_upper_miss), color="b")
+#g.map(sns.scatterplot, 'slice_group', 'clflush_local_hit_n', color="g")
+plt.show()
+
g = sns.FacetGrid(stats, row="main_core_fixed")
g.map(sns.scatterplot, 'slice_group', 'clflush_miss_n', color="b")
diff --git a/requirements.txt b/requirements.txt
index 1ac0819..f2d42cf 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,8 @@
pandas==1.0.3
seaborn==0.10.0
wquantiles==0.5
+
+matplotlib~=3.2.1
+numpy~=1.18.2
+gmpy2~=2.0.8
+scipy~=1.4.1