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The Lounge War Stories Linus Torvalds reply about Meltdown and Spectre. Post 303012275 by Corona688 on Thursday 1st of February 2018 04:07:36 PM
Old 02-01-2018
Quote:
Originally Posted by dodona
I read that with the 4.15 Kernel with build-in patches for the hypothetical problem comes with 15-30% performance loss.
That's way overblown, because the performance loss happens during the switch between userspace and kernelspace. Sensible programs don't spend most of their time doing thousands of tiny system calls.

A 30% reduction in performance there is bad, but not the same as a 30% slower computer.
 

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MPSCNNLossDescriptor(3) 				 MetalPerformanceShaders.framework				   MPSCNNLossDescriptor(3)

NAME
MPSCNNLossDescriptor SYNOPSIS
#import <MPSCNNLoss.h> Inherits NSObject, and <NSCopying>. Instance Methods (nonnull instancetype) - init Class Methods (nullable MPSCNNLossDescriptor *) + cnnLossDescriptorWithType:reductionType: Properties MPSCNNLossType lossType MPSCNNReductionType reductionType float weight float labelSmoothing NSUInteger numberOfClasses float epsilon float delta Detailed Description This depends on Metal.framework. The MPSCNNLossDescriptor specifies a loss filter descriptor. The same descriptor can be used to initialize both the MPSCNNLoss and the MPSCNNLossGradient filters. Method Documentation + (nullable MPSCNNLossDescriptor*) cnnLossDescriptorWithType: (MPSCNNLossType) lossType(MPSCNNReductionType) reductionType Make a descriptor for a MPSCNNLoss or MPSCNNLossGradient object. Parameters: lossType The type of a loss filter. reductionType The type of a reduction operation to apply. This argument is ignored in the MPSCNNLossGradient filter. Returns: A valid MPSCNNLossDescriptor object or nil, if failure. - (nonnull instancetype) init Property Documentation - delta [read], [write], [nonatomic], [assign] The delta parameter. The default value is 1.0f. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossTypeHuber. Given predictions and labels (ground truth), it is applied in the following way: if (|predictions - labels| <= delta, loss = 0.5f * predictions^2 if (|predictions - labels| > delta, loss = 0.5 * delta^2 + delta * (|predictions - labels| - delta) - epsilon [read], [write], [nonatomic], [assign] The epsilon parameter. The default value is 1e-7. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossTypeLog. Given predictions and labels (ground truth), it is applied in the following way: -(labels * log(predictions + epsilon)) - ((1 - labels) * log(1 - predictions + epsilon)) - labelSmoothing [read], [write], [nonatomic], [assign] The label smoothing parameter. The default value is 0.0f. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossFunctionTypeSoftmaxCrossEntropy, MPSCNNLossFunctionTypeSigmoidCrossEntropy. MPSCNNLossFunctionTypeSoftmaxCrossEntropy: given labels (ground truth), it is applied in the following way: labels = labelSmoothing > 0 ? labels * (1 - labelSmoothing) + labelSmoothing / numberOfClasses : labels MPSCNNLossFunctionTypeSigmoidCrossEntropy: given labels (ground truth), it is applied in the following way: labels = labelSmoothing > 0 ? labels * (1 - labelSmoothing) + 0.5 * labelSmoothing : labels - lossType [read], [write], [nonatomic], [assign] The type of a loss filter. This parameter specifies the type of a loss filter. - numberOfClasses [read], [write], [nonatomic], [assign] The number of classes parameter. The default value is 1. This parameter is valid only for the loss functions of the following type(s): MPSCNNLossFunctionTypeSoftmaxCrossEntropy. Given labels (ground truth), it is applied in the following way: labels = labelSmoothing > 0 ? labels * (1 - labelSmoothing) + labelSmoothing / numberOfClasses : labels - reductionType [read], [write], [nonatomic], [assign] The type of a reduction operation performed in the loss filter. This parameter specifies the type of a reduction operation performed in the loss filter. - weight [read], [write], [nonatomic], [assign] The scale factor to apply to each element of a result. Each element of a result is multiplied by the weight value. The default value is 1.0f. Author Generated automatically by Doxygen for MetalPerformanceShaders.framework from the source code. Version MetalPerformanceShaders-100 Thu Feb 8 2018 MPSCNNLossDescriptor(3)
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