End sem 7; week 2 winter session 2025

7th-Semester-Fall-2024/VLSI/labs/lab-5/logical_effort.py

@@ -0,0 +1,33 @@
+import numpy as np
+
+g = np.array([1, 4/3, 4/3, 4/3, 4/3, 4/3, 4/3, 1])
+b = np.array([2, 3, 1, 2, 3, 1, 1, 1])
+p = np.array([1, 2, 2, 2, 2, 2, 2, 1])
+h = np.empty_like(g)
+sizing = np.array([3, 2, 2, 2, 2, 2, 2, 3])
+min_sizing = np.array([3,4,4,4,4,4,4,3])
+
+C_in = np.array([3,0,0,0,0,0,0,0,45], dtype=np.float32)
+
+N = len(C_in) - 1
+H = C_in[-1] / C_in[0]
+G = np.prod(g)
+B = np.prod(b)
+
+P = np.sum(p)
+
+for i in range(4):
+    F = G*B*H
+    f_opt = F**(1/N)
+    D = N*f_opt + P
+    
+    for j in range(N)[::-1]:
+        C_in[j] = g[j]*b[j]*C_in[j+1]/f_opt
+
+    for j in range(N)[::-1]:
+        C_in[j] = np.rint(C_in[j]/sizing[j])*sizing[j]
+        if C_in[j] < min_sizing[j]:
+            C_in[j] = min_sizing[j]
+        h[j] = C_in[j+1] / C_in[j]
+    H = np.prod(h)
+