}
	}
	uaAppend("; ", "")

	if cpus, err := gopsutilcpu.Info(); err == nil && len(cpus) > 0 {
		cpuMap := make(map[string]struct{}, len(cpus))
		coreMap := make(map[string]struct{}, len(cpus))
		for i := range cpus {
			cpuMap[cpus[i].PhysicalID] = struct{}{}
			coreMap[cpus[i].CoreID] = struct{}{}
		}
		cpu := cpus[0]

   * failed CAS on base update), the table is initialized to size 2.
   * The table size is doubled upon further contention until
   * reaching the nearest power of two greater than or equal to the
   * number of CPUS. Table slots remain empty (null) until they are
   * needed.
   *
   * A single spinlock ("busy") is used for initializing and
   * resizing the table, as well as populating slots with new Cells.

   * failed CAS on base update), the table is initialized to size 2.
   * The table size is doubled upon further contention until
   * reaching the nearest power of two greater than or equal to the
   * number of CPUS. Table slots remain empty (null) until they are
   * needed.
   *
   * A single spinlock ("busy") is used for initializing and
   * resizing the table, as well as populating slots with new Cells.

                }
                _defaultParallel = socketToCore.values().stream().mapToInt(i -> i).sum();
            } else if (isMac(project.getProviders())) {
                // Ask macOS to count physical CPUs for us
                ByteArrayOutputStream stdout = new ByteArrayOutputStream();
                project.exec(spec -> {
                    spec.setExecutable("sysctl");
                    spec.args("-n", "hw.physicalcpu");

net.ipv4.tcp_mtu_probing=1
net.ipv4.tcp_base_mss=1280

# Disable ipv6
net.ipv6.conf.all.disable_ipv6=1
net.ipv6.conf.default.disable_ipv6=1
net.ipv6.conf.lo.disable_ipv6=1

[bootloader]
# Avoid firing timers for all CPUs at the same time. This is irrelevant for
# full nohz systems

dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas in previous “parameter server” designs the management of shared state is built into...

        assertThrows(IllegalArgumentException.class, () -> cli.calculateDegreeOfConcurrency("XXXC"));

        int cpus = Runtime.getRuntime().availableProcessors();
        assertEquals((int) (cpus * 2.2), cli.calculateDegreeOfConcurrency("2.2C"));
        assertEquals(1, cli.calculateDegreeOfConcurrency("0.0001C"));

## Recap { #recap }

You can use multiple worker processes with the `--workers` CLI option with the `fastapi` or `uvicorn` commands to take advantage of **multi-core CPUs**, to run **multiple processes in parallel**.

You could use these tools and ideas if you are setting up **your own deployment system** while taking care of the other deployment concepts yourself.

                }
                _defaultParallel = socketToCore.values().stream().mapToInt(i -> i).sum();
            } else if (OS.current() == OS.MAC) {
                // Ask macOS to count physical CPUs for us
                ByteArrayOutputStream stdout = new ByteArrayOutputStream();
                project.exec(spec -> {
                    spec.setExecutable("sysctl");
                    spec.args("-n", "hw.physicalcpu");

- [PRF](#prf): HMAC-SHA-256
- [AEAD](#aead): AES-256-GCM if the CPU supports AES-NI, ChaCha20-Poly1305 otherwise. More specifically AES-256-GCM is only selected for X86-64 CPUs with AES-NI extension.

Further any secret key (apart from the KMS-generated ones) is 256 bits long. The KMS-generated keys may be 256 bits but this depends on the KMS capabilities and configuration.