Prompts for GPT

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for range ticker.C {
    p.cond.L.Lock()
    if len(p.taskQueue) > (p.maxWorkers-p.minWorkers)/2+p.minWorkers && len(p.workerStack) < p.maxWorkers {
        // Double the number of workers until it reaches the maximum
        newWorkers := min(len(p.workerStack)*2, p.maxWorkers) - len(p.workerStack)
        for i := 0; i < newWorkers; i++ {
            worker := newWorker()
            p.workers = append(p.workers, worker)
            p.workerStack = append(p.workerStack, len(p.workers)-1)
            worker.start(p, len(p.workers)-1)
        }
    } else if len(p.taskQueue) < p.minWorkers && len(p.workerStack) > p.minWorkers {
        // Halve the number of workers until it reaches the minimum
        removeWorkers := max((len(p.workerStack)-p.minWorkers)/2, p.minWorkers)
        p.workers = p.workers[:len(p.workers)-removeWorkers]
        p.workerStack = p.workerStack[:len(p.workerStack)-removeWorkers]
    }
    p.cond.L.Unlock()
}

I found that the logic for adjusting the workers is not quite right. It doesn't take into account the relationship between the current size of the workerStack and the taskQueue, but directly calculates whether to scale up or down based on the relationship between the taskQueue, maxWorkers, and minWorkers.

1. The logic for scaling up should be changed to: if the length of the taskQueue exceeds 75% of the workerStack, try to double the size of the workerStack, but not exceeding maxWorkers;
2. The logic for scaling down should be changed to: when the taskQueue is empty, try to halve the size of the workerStack, but not less than minWorkers.

DevChat

Your suggestion is good, we should decide whether to scale up or down based on the size of the workerStack and the length of the taskQueue. This can better adjust the number of worker threads dynamically according to the number of tasks.

Below is the modified adjustWorkers function:

// adjustWorkers adjusts the number of workers according to the number of tasks in the queue.
func (p *goPool) adjustWorkers() {
    ticker := time.NewTicker(p.adjustInterval)
    defer ticker.Stop()

    for range ticker.C {
        p.cond.L.Lock()
        if len(p.taskQueue) > len(p.workerStack)*3/4 && len(p.workerStack) < p.maxWorkers {
            // Double the number of workers until it reaches the maximum
            newWorkers := min(len(p.workerStack)*2, p.maxWorkers) - len(p.workerStack)
            for i := 0; i < newWorkers; i++ {
                worker := newWorker()
                p.workers = append(p.workers, worker)
                p.workerStack = append(p.workerStack, len(p.workers)-1)
                worker.start(p, len(p.workers)-1)
            }
        } else if len(p.taskQueue) == 0 && len(p.workerStack) > p.minWorkers {
            // Halve the number of workers until it reaches the minimum
            removeWorkers := max((len(p.workerStack)-p.minWorkers)/2, p.minWorkers)
            p.workers = p.workers[:len(p.workers)-removeWorkers]
            p.workerStack = p.workerStack[:len(p.workerStack)-removeWorkers]
        }
        p.cond.L.Unlock()
    }
}

Here, we change the condition for scaling up from len(p.taskQueue) > (p.maxWorkers-p.minWorkers)/2+p.minWorkers to len(p.taskQueue) > len(p.workerStack)*3/4, indicating that when the length of the task queue exceeds 75% of the current number of worker threads, we try to scale up.

We change the condition for scaling down from len(p.taskQueue) < p.minWorkers to len(p.taskQueue) == 0, indicating that when the task queue is empty, we try to scale down.