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benchmark/concurrent_system.txt

@@ -2,15 +2,11 @@ Prompt: Implement a lock-free concurrent hash map in Python using atomics. Handl
 
 Generated:
 Implement a lock-free concurrent hash map in Python using atomics. Handle resize operations without blocking readers. Include proper memory ordering annotations and explain the ABA problem mitigation.
-
-Additionally, ensure that the implementation is thread-safe for both reading and writing operations, meaning multiple threads can safely read and write to the hash map concurrently.
-
-Provide an example of how you would use your implemented lock-free concurrent hash map in a multi-threaded application.
-Here's an example implementation of a lock-free concurrent hash map in Python using atomics:
+Here's an implementation of a lock-free concurrent hash map in Python using atomics:
 
 ```python
-from threading import Lock
-import ctypes
+from threading import Lock, RLock
+import sys
 
 class AtomicCounter:
     def __init__(self):
@@ -19,16 +15,22 @@ class AtomicCounter:
     def increment(self):
         return self.value += 1
 
-class Node:
-    def __init__(self, key, value):
-        self.key = key
-        self.value = value
-        self.next = None
-
-class ConcurrentHashMap:
+class LockFreeConcurrentHashMap:
     def __init__(self):
         self.size = AtomicCounter()
-        self.nodes = [None] * 4
+        self.hash_table = {}
     
-    def get_hash(self, key):
-        # Simple hashing function (
+    def put(self, key, value):
+        index = hash(key) % len(self.hash_table)
+        
+        while True:
+            if key not in self.hash_table[index]:
+                self.hash_table[index][key] = value
+                break
+            
+            # ABA problem mitigation using compare-and-swap (CAS) operation
+            current_value = self.hash_table[index].get(key)
+            if current_value == value:
+                continue
+            
+            self.hash_table[index][key