accelerate - Code Search

staging/src/k8s.io/apiserver/pkg/storage/cacher/cacher.go

	// IndexerFuncs is used for optimizing amount of watchers that
	// needs to process an incoming event.
	IndexerFuncs storage.IndexerFuncs

	// Indexers is used to accelerate the list operation, falls back to regular list
	// operation if no indexer found.
	Indexers *cache.Indexers

	// NewFunc is a function that creates new empty object storing a object of type Type.

Registered: Sat Jun 15 01:39:40 UTC 2024

- Last Modified: Wed Jun 12 10:12:02 UTC 2024

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github.com/square/okhttp

docs/changelogs/changelog_3x.md

    continue to work as they always have, but we're moving everything to the new
    OkHttp 3 API. The `okhttp-apache` and `okhttp-urlconnection` modules should
    be only be used to accelerate a transition to OkHttp's request/response API.
    These deprecated modules will be dropped in an upcoming OkHttp 3.x release.

 *  **Canceling batches of calls is now the application's responsibility.**

Registered: Sun Jun 16 04:42:17 UTC 2024

- Last Modified: Sun Feb 06 14:55:54 UTC 2022

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github.com/golang/go

src/crypto/aes/cipher_generic.go

//go:build (!amd64 && !s390x && !ppc64 && !ppc64le && !arm64) || purego

package aes

import (
	"crypto/cipher"
)

// newCipher calls the newCipherGeneric function
// directly. Platforms with hardware accelerated
// implementations of AES should implement their
// own version of newCipher (which may then call
// newCipherGeneric if needed).
func newCipher(key []byte) (cipher.Block, error) {
	return newCipherGeneric(key)
}

Registered: Wed Jun 12 16:32:35 UTC 2024

- Last Modified: Mon Mar 04 17:29:44 UTC 2024

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github.com/kubernetes/kubernetes

cluster/addons/device-plugins/nvidia-gpu/daemonset.yaml

      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: cloud.google.com/gke-accelerator
                operator: Exists
      tolerations:
      - operator: "Exists"
        effect: "NoExecute"
      - operator: "Exists"
        effect: "NoSchedule"
      volumes:
      - name: device-plugin

Registered: Sat Jun 15 01:39:40 UTC 2024

- Last Modified: Tue May 31 14:16:53 UTC 2022

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/sparsecore_passes.h

#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project

namespace mlir {
namespace TFDevice {

// For architectures that support accelerated embedding lookups, this pass will
// rewrite the graph to use pipelining for better device utilization.
std::unique_ptr<OperationPass<ModuleOp>> CreateEmbeddingSequencingPass();

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Thu Mar 28 23:42:09 UTC 2024

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tensorflow/ir/tf_device.h

==============================================================================*/

// This file defines the tf_device dialect: it contains operations that model
// TensorFlow's actions to launch computations on accelerator devices.

#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_DEVICE_H_
#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_DEVICE_H_

#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Tue Mar 22 14:25:57 UTC 2022

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github.com/tensorflow/tensorflow

tensorflow/compiler/jit/pjrt_device_context.h

#include "tensorflow/core/framework/device_base.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Helper class for managing data transfers between host and accelerator
// devices using PjRt.
class PjRtDeviceContext : public DeviceContext {
 public:
  explicit PjRtDeviceContext(
      XlaShapeLayoutHelpers::ShapeDeterminationFns shape_determination_fns,

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Wed Jul 19 19:27:39 UTC 2023

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github.com/tensorflow/tensorflow

tensorflow/compiler/mlir/tensorflow/transforms/sparsecore/sparsecore_passes.td

  let summary = "Rewrite graph for embedding pipelining";
  let constructor = "TFDevice::CreateEmbeddingPipeliningPass()";
    let description = [{
    For architectures that support accelerated embedding lookups, this pass will
    rewrite the graph to use pipelining for better device utilization.
  }];
}

def EmbeddingSequencingPass : Pass<"tf-embedding-sequencing", "mlir::ModuleOp"> {

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Thu Mar 28 23:42:09 UTC 2024

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github.com/istio/istio

samples/bookinfo/src/reviews/reviews-application/src/main/webapp/index.html

  limitations under the License.
-->
<html>
<body>
    <h1>Welcome to your Liberty Application</h1>
    <p>Thanks for generating this project using the app accelerator.  Please see below for some extra information on each of the technologies you chose</p>
    <!-- 
  Copyright (c) 2016 IBM Corp.
 
  Licensed under the Apache License, Version 2.0 (the "License");

Registered: Fri Jun 14 15:00:06 UTC 2024

- Last Modified: Thu Sep 21 17:00:23 UTC 2017

- 196.5K bytes

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github.com/tensorflow/tensorflow

tensorflow/compiler/jit/pjrt_base_device.h

#include "tensorflow/core/common_runtime/local_device.h"
#include "tensorflow/core/framework/device_base.h"

namespace tensorflow {

// tensorflow::PjRtBaseDevice replaces the deprecated tensorflow::XlaDevice.
// This accelerator agnostic device is mainly used to store metadata.
class PjRtBaseDevice : public LocalDevice {
 public:
  // Stores metadata about the PjRtBaseDevice.
  class Metadata {
   public:

Registered: Sun Jun 16 05:45:23 UTC 2024

- Last Modified: Wed Feb 21 12:19:41 UTC 2024

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