*
     * @param cfg the configuration containing machine ID
     */
    public AvSingleHost(final Configuration cfg) {
        this(new byte[8], cfg.getMachineId());
    }

    /**
     * Constructs an AvSingleHost with custom data and machine ID
     *
     * @param customData custom data for the single host (8 bytes)
     * @param machineId the machine identifier (32 bytes)
     */

  Remove-Item $zulu_zip; \
  $env:PATH = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\") + \";${zulu_root}\\bin\"; \
  [Environment]::SetEnvironmentVariable(\"PATH\", $env:PATH, \"Machine\"); \
  $env:JAVA_HOME = $zulu_root; \
  [Environment]::SetEnvironmentVariable(\"JAVA_HOME\", $env:JAVA_HOME, \"Machine\")

# Point to the LLVM installation.
# The Bazel Windows guide claims it can find LLVM automatically,

     * Should correctly encode custom data and machine ID.
     */
    @Test
    void testAvSingleHostCustomDataMachineIdConstructor() {
        byte[] customData = new byte[8];
        customData[0] = 0x01;
        customData[7] = 0x08;

        byte[] machineId = new byte[32];
        machineId[0] = 0x10;
        machineId[31] = 0x20;

## Server Machine and Server Program { #server-machine-and-server-program }

There's a small detail about names to keep in mind. 💡

The word "**server**" is commonly used to refer to both the remote/cloud computer (the physical or virtual machine) and also the program that is running on that machine (e.g. Uvicorn).

## Caso de Uso

Empecemos con un ejemplo de **caso de uso** y luego veamos cómo resolverlo con esto.

Imaginemos que tienes algunos **modelos de machine learning** que quieres usar para manejar requests. 🤖

		}
	}

	return host, port, nil
}

// isLocalHost - checks if the given parameter
// correspond to one of the local IP of the
// current machine
func isLocalHost(host string, port string, localPort string) (bool, error) {
	hostIPs, err := getHostIP(host)
	if err != nil {
		return false, err
	}

	nonInterIPV4s := mustGetLocalIP4().Intersection(hostIPs)

### Concurrency + Parallelism: Web + Machine Learning { #concurrency-parallelism-web-machine-learning }

With **FastAPI** you can take advantage of concurrency that is very common for web development (the same main attraction of NodeJS).

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

Lorsqu'on se réfère à la machine distante, il est courant de l'appeler **serveur**, mais aussi **machine**, **VM** (machine virtuelle), **nœud**. Tout cela fait référence à un type de machine distante, exécutant  Linux, en règle générale, sur laquelle vous exécutez des programmes.


## Installer le programme serveur

Vous pouvez installer un serveur compatible ASGI avec :

//// tab | Uvicorn

+  __attribute__ ((__alloc_size__ params))
+
 #include <iostream>
 
 using namespace std;
diff --git a/sysdeps/aarch64/dl-machine.h b/sysdeps/aarch64/dl-machine.h
index 185402f..bbdeae0 100644
--- a/sysdeps/aarch64/dl-machine.h
+++ b/sysdeps/aarch64/dl-machine.h
@@ -49,23 +49,11 @@ elf_machine_load_address (void)
   /* To figure out the load address we use the definition that for any symbol:

  Remove-Item $zulu_zip; \
  $env:PATH = [Environment]::GetEnvironmentVariable(\"PATH\", \"Machine\") + \";${zulu_root}\\bin\"; \
  [Environment]::SetEnvironmentVariable(\"PATH\", $env:PATH, \"Machine\"); \
  $env:JAVA_HOME = $zulu_root; \
  [Environment]::SetEnvironmentVariable(\"JAVA_HOME\", $env:JAVA_HOME, \"Machine\")

# Point to the LLVM installation.
# The Bazel Windows guide claims it can find LLVM automatically,