Startonix / Modular-AI

Advanced AI Training and Building Repository
0 stars 0 forks source link

Parallel Processing Optimization #164

Open Startonix opened 1 month ago

Startonix commented 1 month ago

parallel_processing_optimization.py

from concurrent.futures import ThreadPoolExecutor

def simulate_parallel_processing(task_function, data_chunks): with ThreadPoolExecutor(max_workers=4) as executor: results = executor.map(task_function, data_chunks) return list(results)

def example_parallel_task(data_chunk): return sum(data_chunk)

data_chunks = [list(range(1000000)), list(range(1000000, 2000000))] parallel_results = simulate_parallel_processing(example_parallel_task, data_chunks) print("Parallel Results:", parallel_results)