"""
Simple parallel array distributor for tensor operations
"""

import numpy as np
from typing import List, Optional

class ParallelArrayDistributor:
    """Distributes array operations across multiple streaming multiprocessors"""
    
    def __init__(self, num_sms: int = 108, cores_per_sm: int = 3000):
        self.num_sms = num_sms
        self.cores_per_sm = cores_per_sm
        
    def distribute(self, data: np.ndarray) -> List[np.ndarray]:
        """
        Distribute data across SMs for parallel processing
        
        Args:
            data: Input array to distribute
            
        Returns:
            List of array chunks, one per SM
        """
        # Calculate chunk size
        total_size = data.shape[0]
        chunk_size = total_size // self.num_sms
        if chunk_size == 0:
            chunk_size = 1
            
        # Split data into chunks
        chunks = []
        for i in range(0, total_size, chunk_size):
            end = min(i + chunk_size, total_size)
            chunks.append(data[i:end])
            
        # Pad with empty arrays if needed
        while len(chunks) < self.num_sms:
            chunks.append(np.array([]))
            
        return chunks