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Found 4 papers, 0 papers with code
Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks
In this paper, we present an in-depth analysis of methods for maximizing the sparsity of the activations in a trained neural network, and show that, when coupled with an efficient sparse-input convolution algorithm, we can leverage this sparsity for significant performance gains.
Be Prepared When Network Goes Bad: An Asynchronous View-Change Protocol
The state-of-the-art partially synchronous BFT SMR protocols provide optimal linear communication cost per decision under synchrony and good leaders, but lose liveness under asynchrony.
Distributed, Parallel, and Cluster Computing Cryptography and Security
Fast Graphical Population Protocols
Let $G$ be a graph on $n$ nodes.
Distributed, Parallel, and Cluster Computing Data Structures and Algorithms
L3 Fusion: Fast Transformed Convolutions on CPUs
Fast convolutions via transforms, either Winograd or FFT, had emerged as a preferred way of performing the computation of convolutional layers, as it greatly reduces the number of required operations.
