简单地将整个内容替换为:

return File.ReadAllBytes(fileName);

但是，如果您关心内存消耗，就不应该将整个文件一次全部读入内存。你应该分块做。

In case with 'a large file' is meant beyond the 4GB limit, then my following written code logic is appropriate. The key issue to notice is the LONG data type used with the SEEK method. As a LONG is able to point beyond 2^32 data boundaries. In this example, the code is processing first processing the large file in chunks of 1GB, after the large whole 1GB chunks are processed, the left over (<1GB) bytes are processed. I use this code with calculating the CRC of files beyond the 4GB size. (using https://crc32c.machinezoo.com/ for the crc32c calculation in this example)

private uint Crc32CAlgorithmBigCrc(string fileName)
{
    uint hash = 0;
    byte[] buffer = null;
    FileInfo fileInfo = new FileInfo(fileName);
    long fileLength = fileInfo.Length;
    int blockSize = 1024000000;
    decimal div = fileLength / blockSize;
    int blocks = (int)Math.Floor(div);
    int restBytes = (int)(fileLength - (blocks * blockSize));
    long offsetFile = 0;
    uint interHash = 0;
    Crc32CAlgorithm Crc32CAlgorithm = new Crc32CAlgorithm();
    bool firstBlock = true;
    using (FileStream fs = new FileStream(fileName, FileMode.Open, FileAccess.Read))
    {
        buffer = new byte[blockSize];
        using (BinaryReader br = new BinaryReader(fs))
        {
            while (blocks > 0)
            {
                blocks -= 1;
                fs.Seek(offsetFile, SeekOrigin.Begin);
                buffer = br.ReadBytes(blockSize);
                if (firstBlock)
                {
                    firstBlock = false;
                    interHash = Crc32CAlgorithm.Compute(buffer);
                    hash = interHash;
                }
                else
                {
                    hash = Crc32CAlgorithm.Append(interHash, buffer);
                }
                offsetFile += blockSize;
            }
            if (restBytes > 0)
            {
                Array.Resize(ref buffer, restBytes);
                fs.Seek(offsetFile, SeekOrigin.Begin);
                buffer = br.ReadBytes(restBytes);
                hash = Crc32CAlgorithm.Append(interHash, buffer);
            }
            buffer = null;
        }
    }
    //MessageBox.Show(hash.ToString());
    //MessageBox.Show(hash.ToString("X"));
    return hash;
}

Depending on the frequency of operations, the size of the files, and the number of files you're looking at, there are other performance issues to take into consideration. One thing to remember, is that each of your byte arrays will be released at the mercy of the garbage collector. If you're not caching any of that data, you could end up creating a lot of garbage and be losing most of your performance to % Time in GC. If the chunks are larger than 85K, you'll be allocating to the Large Object Heap(LOH) which will require a collection of all generations to free up (this is very expensive, and on a server will stop all execution while it's going on). Additionally, if you have a ton of objects on the LOH, you can end up with LOH fragmentation (the LOH is never compacted) which leads to poor performance and out of memory exceptions. You can recycle the process once you hit a certain point, but I don't know if that's a best practice.

关键是，在以最快的方式将所有字节读入内存之前，你应该考虑应用程序的整个生命周期，否则你可能会以整体性能换取短期性能。

简单地将整个内容替换为:

return File.ReadAllBytes(fileName);

但是，如果您关心内存消耗，就不应该将整个文件一次全部读入内存。你应该分块做。

用这个:

 bytesRead = responseStream.ReadAsync(buffer, 0, Length).Result;

如果您正在处理大于2 GB的文件，您会发现上述方法失败。

直接将流交给MD5并允许它为你分块文件要容易得多:

private byte[] computeFileHash(string filename)
{
    MD5 md5 = MD5.Create();
    using (FileStream fs = new FileStream(filename, FileMode.Open))
    {
        byte[] hash = md5.ComputeHash(fs);
        return hash;
    }
}