import math


def num_splits_heuristic(total_mblocks, num_SMs, num_n_blocks, num_m_blocks, size_one_kv_head, is_causal_or_local, max_splits):
    """
    Determines the optimal number of splits for maximizing GPU occupancy while balancing memory efficiency.

    Parameters:
    - total_mblocks (int): Total number of m_blocks.
    - num_SMs (int): Number of Streaming Multiprocessors (SMs) in the GPU.
    - num_n_blocks (int): Number of n_blocks.
    - num_m_blocks (int): Number of m_blocks.
    - size_one_kv_head (int): Size of one KV head in bytes.
    - is_causal_or_local (bool): Indicates whether the operation is causal or local.
    - max_splits (int): Maximum number of allowed splits.

    Returns:
    - int: The optimal number of splits.
    """
    # If we have enough m_blocks to almost fill the SMs, prefer 1 split unless memory constraints apply.
    if total_mblocks >= 0.8 * num_SMs:
        size_l2 = 50 * 1024 * 1024  # L2 cache size assumption (50MB)
        # Only split if each KV head is too large for L2 and there are enough m_blocks
        if size_one_kv_head > size_l2 and num_m_blocks >= num_SMs * 2 and not is_causal_or_local:
            return min((size_one_kv_head + size_l2 - 1) // size_l2, max_splits)
        else:
            return 1

    # If num_n_blocks is too small, we don't split
    if num_n_blocks <= 4:
        return 1

    # Limit max_splits to a reasonable range
    max_splits = min(max_splits, num_SMs, num_n_blocks)

    max_efficiency = 0.0
    efficiency = []

    # Compute efficiency for different splits
    for num_splits in range(1, max_splits + 1):
        n_waves = (total_mblocks * num_splits) / num_SMs
        eff = n_waves / math.ceil(n_waves)
        # Track max efficiency
        if eff > max_efficiency:
            max_efficiency = eff

        efficiency.append(eff)

    # Find the smallest number of splits that achieves at least 85% of max efficiency
    for num_splits in range(1, max_splits + 1):
        if efficiency[num_splits - 1] >= 0.85 * max_efficiency:
            return num_splits

    return 1
