KLMD	R2, R8                 // b93f0028
	KIMD	R0, R4                 // b93e0004
	KDSA	R0, R8                 // b93a0008
	KMA	R2, R6, R4             // b9296024
	KMCTR   R2, R6, R4             // b92d6024

	// vector add and sub instructions
	VAB	V3, V4, V4              // e743400000f3
	VAH	V3, V4, V4              // e743400010f3
	VAF	V3, V4, V4              // e743400020f3
	VAG	V3, V4, V4              // e743400030f3

      }
      flowControlListener.receivingConnectionWindowChanged(readBytes)
    }
  }

  /**
   * Returns a new server-initiated stream.
   *
   * @param associatedStreamId the stream that triggered the sender to create this stream.
   * @param out true to create an output stream that we can use to send data to the remote peer.
   *     Corresponds to `FLAG_FIN`.
   */
  @Throws(IOException::class)
  fun pushStream(

import org.codelibs.fess.unit.UnitFessTestCase;
import org.codelibs.fess.util.ComponentUtil;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.TestInfo;
import org.lastaflute.web.response.render.RenderData;
import org.lastaflute.web.validation.VaMessenger;

public class AdminSearchlistActionTest extends UnitFessTestCase {

    @Override
    protected void setUp(TestInfo testInfo) throws Exception {

        queue[parentIndex] = x;
        return parentIndex;
      }
      queue[index] = x;
      return index;
    }

    // About the term "aunt node": it's better to leave gender out of it, but for this the English
    // language has nothing for us. Except for the whimsical neologism "pibling" (!) which we
    // obviously could not expect to increase anyone's understanding of the code.

    /**

		// Returning error here is too noisy.
		return nil
	case c.outQueue <- msg:
		return nil
	}
}

// queueMsg queues a message, with an optional payload.
// sender should not reference msg.Payload
func (c *Connection) queueMsg(msg message, payload sender) error {
	// Add baseflags.
	msg.Flags.Set(c.baseFlags)
	// This cannot encode subroute.
	msg.Flags.Clear(FlagSubroute)
	if payload != nil {

        queue[parentIndex] = x;
        return parentIndex;
      }
      queue[index] = x;
      return index;
    }

    // About the term "aunt node": it's better to leave gender out of it, but for this the English
    // language has nothing for us. Except for the whimsical neologism "pibling" (!) which we
    // obviously could not expect to increase anyone's understanding of the code.

    /**

* **Maschinelles Lernen**: Normalerweise sind viele „Matrix“- und „Vektor“-Multiplikationen erforderlich. Stellen Sie sich eine riesige Tabelle mit Zahlen vor, in der Sie alle Zahlen gleichzeitig multiplizieren.

            this.updateCalendars();

            //update the form inputs above the calendars with the new time
            this.updateFormInputs();

            //re-render the time pickers because changing one selection can affect what's enabled in another
            this.renderTimePicker('left');
            this.renderTimePicker('right');

        },

		for {
			tok = p.nextToken()
			if len(operands) == 0 && len(items) == 0 {
				if p.arch.InFamily(sys.ARM, sys.ARM64, sys.AMD64, sys.I386, sys.Loong64, sys.RISCV64) && tok == '.' {
					// Suffixes: ARM conditionals, Loong64 vector instructions, RISCV rounding mode or x86 modifiers.
					tok = p.nextToken()
					str := p.lex.Text()
					if tok != scanner.Ident {
						p.errorf("instruction suffix expected identifier, found %s", str)
					}

---

CPU bound 작업의 흔한 예시는 복잡한 수학 처리가 필요한 것들입니다.

예를 들어:

* **오디오** 또는 **이미지** 처리
* **컴퓨터 비전**: 이미지는 수백만 개의 픽셀로 구성되며, 각 픽셀은 3개의 값/색을 갖습니다. 보통 그 픽셀들에 대해 동시에 무언가를 계산해야 합니다.
* **머신러닝**: 보통 많은 "matrix"와 "vector" 곱셈이 필요합니다. 숫자가 있는 거대한 스프레드시트를 생각하고, 그 모든 수를 동시에 곱한다고 생각해보세요.
* **딥러닝**: 머신러닝의 하위 분야이므로 동일하게 적용됩니다. 다만 곱해야 할 숫자가 있는 스프레드시트가 하나가 아니라, 아주 큰 집합이며, 많은 경우 그 모델을 만들고/또는 사용하기 위해 특별한 프로세서를 사용합니다.