### Ist Nebenläufigkeit besser als Parallelität?

Nein! Das ist nicht die Moral der Geschichte.

 * weak references.
 *
 * <p><strong>Performance</strong>
 *
 * <p>The extra bookkeeping done by cycle detecting locks comes at some cost to performance.
 * Benchmarks (as of December 2011) show that:
 *
 * <ul>
 *   <li>for an unnested {@code lock()} and {@code unlock()}, a cycle detecting lock takes 38ns as
 *       opposed to the 24ns taken by a plain lock.

這種類型的非同步性正是 NodeJS 成功的原因（儘管 NodeJS 不是平行的），這也是 Go 語言作為程式語言的一個強大優勢。

這與 **FastAPI** 所能提供的性能水平相同。

你可以同時利用並行性和平行性，進一步提升效能，這比大多數已測試的 NodeJS 框架都更快，並且與 Go 語言相當，而 Go 是一種更接近 C 的編譯語言（<a href="https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1" class="external-link" target="_blank">感謝 Starlette</a>）。

### 並行比平行更好嗎？

不是的！這不是故事的本意。

그리고 **FastAPI**를 사용함으로써 동일한 성능을 낼 수 있습니다.

또한 병렬성과 비동기성을 동시에 사용할 수 있기 때문에, 대부분의 테스트가 완료된 NodeJS 프레임워크보다 더 높은 성능을 얻고 C에 더 가까운 컴파일 언어인 Go와 동등한 성능을 얻을 수 있습니다<a href="https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1" class="external-link" target="_blank">(모두 Starlette 덕분입니다)</a>.

### 동시성이 병렬성보다 더 나은가?

그렇지 않습니다! 그것이 이야기의 교훈은 아닙니다.

そして、それは**FastAPI**で得られるパフォーマンスと同じレベルです。

また、並列処理と非同期処理を同時に実行できるため、テスト済みのほとんどのNodeJSフレームワークよりも高く、Goと同等のパフォーマンスが得られます。Goは、Cに近いコンパイル言語です <a href="https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1" class="external-link" target="_blank">(Starletteに感謝します)</a>。

### 並行は並列よりも優れていますか？

いや！それはこの話の教訓ではありません。

// This makes it easy to run the TestServer from any of the tests.
// Using this interface, functionalities to be used in tests can be
// made generalized, and can be integrated in benchmarks/unit tests/go check suite tests.
type TestErrHandler interface {
	testing.TB
}

const (
	// ErasureSDStr is the string which is used as notation for Single node ObjectLayer in the unit tests.

	// md5sum of the data to written is required as input for PutObject.

	md5hex := getMD5Hash(textData)
	sha256hex := ""

	// benchmark utility which helps obtain number of allocations and bytes allocated per ops.
	b.ReportAllocs()
	// the actual benchmark for PutObject starts here. Reset the benchmark timer.

	for i := 0; b.Loop(); i++ {
		// insert the object.
		objInfo, err := obj.PutObject(b.Context(), bucket, "object"+strconv.Itoa(i),

Gunicornと組み合わせることで、非同期でマルチプロセスなサーバーを持つことがきます。

詳細は[デプロイ](deployment/index.md){.internal-link target=_blank}の項目で確認してください。

///

## ベンチマーク と スピード

			if r != needle {
				rs = append(rs, r)
			}
		}
	}
	// Shuffle the runes so that they are not in descending order.
	// The sort is deterministic since this is used for benchmarks,
	// which need to be repeatable.
	rr := rand.New(rand.NewSource(1))
	rr.Shuffle(len(rs), func(i, j int) {
		rs[i], rs[j] = rs[j], rs[i]
	})
	uchars := string(rs)

	return func(b *testing.B, n int) {

*   Python 3.3+ support via changes to python codebase and ability to specify
    python version via ./configure.

*   Some improvements to GPU performance and memory usage:
    [convnet benchmarks](https://github.com/soumith/convnet-benchmarks/issues/66)
    roughly equivalent with native cudnn v2 performance. Improvements mostly due
    to moving to 32-bit indices, faster shuffling kernels. More improvements to
    come in later releases.