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Optimal Order of One-Point and Multipoint Iteration
TLDR
It is proved that the optimal order of one general class of multipoint iterations is 2 and that an upper bound on the order of a multipoint iteration based on n evaluations of ƒ (no derivatives) is 2.
On Optimistic Methods for Concurrency Control
TLDR
In this paper, two families of nonlocking concurrency controls are presented and the methods used are "optimistic" in the sense that they rely mainly on transaction backup as a control mechanism, “hoping” that conflicts between transactions will not occur.
A Regular Layout for Parallel Adders
TLDR
It is shown that addition of n-bit binary numbers can be performed on a chip with a regular layout in time proportional to log n and with area proportional to n.
I/O complexity: The red-blue pebble game
TLDR
Using the red-blue pebble game formulation, a number of lower bound results for the I/O requirement are proven and may provide insight into the difficult task of balancing I/o and computation in special-purpose system designs.
BranchyNet: Fast inference via early exiting from deep neural networks
TLDR
The BranchyNet architecture is presented, a novel deep network architecture that is augmented with additional side branch classifiers that can both improve accuracy and significantly reduce the inference time of the network.
Why systolic architectures?
TLDR
The basic principle of systolic architectures is reviewed and it is explained why they should result in cost-effective, highperformance special-purpose systems for a wide range of problems.
On Finding the Maxima of a Set of Vectors
TLDR
The problem of finding all maximal elements of V with respect to the partial ordering is considered and the computational com- plexity of the problem is defined to be the number of required comparisons of two components and is denoted by Cd(n).
Systolic Arrays for (VLSI).
TLDR
A systolic system is a network of processors which rhythmically compute and pass data through the system, and almost all processors used in the networks are identical, so that a regular flow of data is kept up in the network.
Distributed Deep Neural Networks Over the Cloud, the Edge and End Devices
TLDR
Compared with the traditional method of offloading raw sensor data to be processed in the cloud, DDNN locally processes most sensor data on end devices while achieving high accuracy and is able to reduce the communication cost by a factor of over 20x.
Fast Algorithms for Manipulating Formal Power Series
TLDR
This paper shows that the composition and reversion problems are equivalent (up to constant factors), and gives algorithms which require only order (n log n) ~/2 operations in many cases of practical importance.
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