## Ports {#ports}

### Linux {#linux}

As [announced](go1.23#linux) in the Go 1.23 release notes, Go 1.24 requires Linux
kernel version 3.2 or later.

### WebAssembly {#wasm}

      tar -C "${TARGET}" -xvzf "libc6-dev_2.17-0ubuntu5.1_amd64/data.tar.gz" && \
      rm -rf "libc6-dev_2.17-0ubuntu5.1_amd64.deb" "libc6-dev_2.17-0ubuntu5.1_amd64"
  ;;
esac

# Put the current kernel headers from ubuntu in place.
ln -s "/usr/include/linux" "/${TARGET}/usr/include/linux"
ln -s "/usr/include/asm-generic" "/${TARGET}/usr/include/asm-generic"
ln -s "/usr/include/x86_64-linux-gnu/asm" "/${TARGET}/usr/include/asm"

   *       then sequentially accessing it could result in other processes dying. This is solvable
   *       via madvise(2), but that obviously doesn't exist in java.
   *   <li>Ordinary copy. Kernel copies bytes into a kernel buffer, from a kernel buffer into a
   *       userspace buffer (byte[] or ByteBuffer), then copies them from that buffer into the
   *       destination channel.
   * </ol>
   *

		_ = setMaxResources(globalServerCtxt)
	})

	// Verify kernel release and version.
	if oldLinux() {
		warnings = append(warnings, color.YellowBold("Detected Linux kernel version older than 4.0 release, there are some known potential performance problems with this kernel version. MinIO recommends a minimum of 4.x linux kernel version for best performance"))
	}

	maxProcs := runtime.GOMAXPROCS(0)

  // TODO(tfrt-devs): Figure out a way to deprecate following features after
  // migrated to TFRT.
  //===--------------------------------------------------------------------===//
  // Clear pending nodes in thread executors and kernel caches.
  virtual void ClearCachesAndThreadExecutors() = 0;

  // Initialize the step resource container for a training step. This is used
  // in current TF runtime. For tfrt, it is used by fallback op handler.

# Only include debug info for files under tensorflow/, excluding kernels, to
# reduce the size of the debug info in the binary. This is because if the debug
# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g

	if err != nil {
		buf, err = os.ReadFile(cgroupV1MemLimitFile)
	}
	if err != nil {
		return 0
	}
	limit, err = strconv.ParseUint(strings.TrimSpace(string(buf)), 10, 64)
	if err != nil {
		// The kernel can return valid but non integer values
		// but still, no need to interpret more
		return 0
	}
	if limit >= 100*humanize.TiByte {
		// No limit set, or unreasonably high. Ignore
		return 0
	}
	return limit
}

Go 1.22 changed how the runtime interacts with transparent huge pages on Linux.
In particular, a common default Linux kernel configuration can result in
significant memory overheads, and Go 1.22 no longer works around this default.
To work around this issue without adjusting kernel settings, transparent huge
pages can be disabled for Go memory with the
[`disablethp` setting](/pkg/runtime#hdr-Environment_Variable).

        mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],

  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph