Add Matrix-based Benchmark

LunaDB Example/LunaDBManager.py

@@ -0,0 +1,9 @@
+from LunaDB import LunaDB
+
+db = LunaDB('db.json')
+collection = db.table("Blockchain", id_field="id")
+
+collection.insert({"id": 1,"city": "Semarang"})
+collection.insert({"id": 2,"city": "Jakarta"})
+
+print(db)

Matrix-based Benchmark/MatrixBench.py

@@ -0,0 +1,53 @@
+import numpy as np
+from tqdm import tqdm
+from time import time
+
+class MatrixBench():
+    def __init__(self, iters: int, size: int):
+        self.iters = iters
+        self.size = size
+        self.average = 0
+        self.start_time = 0
+        self.end_time = 0
+        self.elapsed_time = 0
+        self.flops:float = 0.0
+
+    def create_matrices(self):
+        # Create num x num matrix and an num x 1 vector with random floating point numbers
+        self.matrix_A = np.random.rand(self.size, self.size).astype(np.float32)
+        self.matrix_B = np.random.rand(self.size).astype(np.float32)
+    
+    def do_operation(self):
+        # Do Floating Point Operation
+        self.start_time = time()
+        _ = np.linalg.solve(self.matrix_A, self.matrix_B)
+        self.end_time = time()
+
+    def do_calculate(self):
+        # Calculate Floating Point Operation per Second (FLOPS)
+        self.elapsed_time = self.end_time - self.start_time
+        self.num_operations = (2 / 3) * self.size **3
+        self.flops = self.num_operations / self.elapsed_time
+        self.average += self.flops
+        
+    def run(self):
+        print("# Linpack-like Matrix-based Floating Point Benchmark #")
+        for i in tqdm(range(self.iters), desc="Running Matrix-based Benchmark..."):
+            self.create_matrices()
+            self.do_operation()
+            self.do_calculate()
+        self.avg_flops: float = (self.average/self.iters) / 1000000
+        print(f"Result : {self.avg_flops:.2f} MFLOPS")
+
+
+def main():
+    # Adjust Matrix Size
+    size = 192
+    # Adjust Iteration Time
+    iters = 10000
+    # Run Benchmark
+    bench = MatrixBench(iters=iters, size=size)
+    bench.run()
+    
+    
+main()

README.md

@@ -3,7 +3,8 @@
 This repository contains useful programs written in **Python 3.9**. Each folder accompanied with **requirements.txt** for easier dependency access.
 
 ## Currently Available: ##
-* Benchmark Program : using **psutil** to obtain performance
-* Pickle Compress Program : compress variable dumps using **gzip**, **bzip2**, **lzma**, or **no compression at all**
-* FastAPI Simple Example (Normal Request, GET Request, HTML Request)
+* **Benchmark Program** : using **psutil** to obtain computer performance
+* **Pickle Compress Program** : compress variable dumps using **gzip**, **bzip2**, **lzma**, or **no compression at all**
+* **FastAPI Simple Example** : contains API standard operations (Normal Request, GET Request, HTML Request)
+* **Matrix-based Bencmark** : contains a class to recreate Linpack (Matrix-based) Floating-point Per Second (FLOPS) Benchmark. Based on **numpy** lib
 * *adding more soon*