The goal of precipitation nowcasting is to predict the future rainfall intensity in a local region over a relatively short period of time. Very few previous studies have examined this crucial and challenging weather forecasting problem from the machine learning perspective. In this paper, we formulate precipitation nowcasting as a spatiotemporal sequence forecasting problem in which both the input and the prediction target are spatiotemporal sequences. By extending the fully connected LSTM (FC-LSTM) to have convolutional structures in both the input-to-state and state-to-state transitions, we propose the convolutional LSTM (ConvLSTM) and use it to build an end-to-end trainable model for the precipitation nowcasting problem. Experiments show that our ConvLSTM network captures spatiotemporal correlations better and consistently outperforms FC-LSTM and the state-of-the-art operational ROVER algorithm for precipitation nowcasting.

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

In Distributed Algorithms, Nancy Lynch provides a blueprint for designing, implementing, and analyzing distributed algorithms. She directs her book at a wide audience, including students, programmers, system designers, and researchers.



Distributed Algorithms contains the most significant algorithms and impossibility results in the area, all in a simple automata-theoretic setting. The algorithms are proved correct, and their complexity is analyzed according to precisely defined complexity measures. The problems covered include resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election, global snapshots, and many others.



The material is organized according to the system model-first by the timing model and then by the interprocess communication mechanism. The material on system models is isolated in separate chapters for easy reference.



The presentation is completely rigorous, yet is intuitive enough for immediate comprehension. This book familiarizes readers with important problems, algorithms, and impossibility results in the area: readers can then recognize the problems when they arise in practice, apply the algorithms to solve them, and use the impossibility results to determine whether problems are unsolvable. The book also provides readers with the basic mathematical tools for designing new algorithms and proving new impossibility results. In addition, it teaches readers how to reason carefully about distributed algorithms-to model them formally, devise precise specifications for their required behavior, prove their correctness, and evaluate their performance with realistic measures.


Table of Contents

1 Introduction 
2 Modelling I; Synchronous Network Model 
3 Leader Election in a Synchronous Ring 
4 Algorithms in General Synchronous Networks 
5 Distributed Consensus with Link Failures 
6 Distributed Consensus with Process Failures 
7 More Consensus Problems 
8 Modelling II: Asynchronous System Model 
9 Modelling III: Asynchronous Shared Memory Model 
10 Mutual Exclusion 
11 Resource Allocation 
12 Consensus 
13 Atomic Objects 
14 Modelling IV: Asynchronous Network Model 
15 Basic Asynchronous Network Algorithms 
16 Synchronizers 
17 Shared Memory versus Networks 
18 Logical Time 
19 Global Snapshots and Stable Properties 
20 Network Resource Allocation 
21 Asynchronous Networks with Process Failures 
22 Data Link Protocols 
23 Partially Synchronous System Models 
24 Mutual Exclusion with Partial Synchrony 
25 Consensus with Partial Synchrony

Distributed algorithms

/pdf/convolutional-lstm-network-a-machine-learning-approach-for-3mrj9pedfq.pdf

Convolutional LSTM Network: a machine learning approach for precipitation nowcasting

Multiagent systems are made up of multiple interacting intelligent agents -- computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care This book offers a state-of-the-art introduction to multiagent systems, covering the field in both breadth and depth, and treating both theory and practice It is suitable for classroom use or independent study This second edition has been completely revised, capturing the tremendous developments in multiagent systems since the first edition appeared in 1999 Sixteen of the book's seventeen chapters were written for this edition; all chapters are by leaders in the field, with each author contributing to the broad base of knowledge and experience on which the book rests The book covers basic concepts of computational agency from the perspective of both individual agents and agent organizations; communication among agents; coordination among agents; distributed cognition; development and engineering of multiagent systems; and background knowledge in logics and game theory Each chapter includes references, many illustrations and examples, and exercises of varying degrees of difficulty The chapters and the overall book are designed to be self-contained and understandable without additional material Supplemental resources are available on the book's Web site Contributors:Rafael Bordini, Felix Brandt, Amit Chopra, Vincent Conitzer, Virginia Dignum, Jurgen Dix, Ed Durfee, Edith Elkind, Ulle Endriss, Alessandro Farinelli, Shaheen Fatima, Michael Fisher, Nicholas R Jennings, Kevin Leyton-Brown, Evangelos Markakis, Lin Padgham, Julian Padget, Iyad Rahwan, Talal Rahwan, Alex Rogers, Jordi Sabater-Mir, Yoav Shoham, Munindar P Singh, Kagan Tumer, Karl Tuyls, Wiebe van der Hoek, Laurent Vercouter, Meritxell Vinyals, Michael Winikoff, Michael Wooldridge, Shlomo Zilberstein

Multiagent Systems

From the Publisher:
Among the many approaches to formal reasoning about programs, Dynamic Logic enjoys the singular advantage of being strongly related to classical logic. Its variants constitute natural generalizations and extensions of classical formalisms. For example, Propositional Dynamic Logic (PDL) can be described as a blend of three complementary classical ingredients: propositional calculus, modal logic, and the algebra of regular events. In First-Order Dynamic Logic (DL), the propositional calculus is replaced by classical first-order predicate calculus. Dynamic Logic is a system of remarkable unity that is theoretically rich as well as of practical value. It can be used for formalizing correctness specifications and proving rigorously that those specifications are met by a particular program. Other uses include determining the equivalence of programs, comparing the expressive power of various programming constructs, and synthesizing programs from specifications. 
This book provides the first comprehensive introduction to Dynamic Logic. It is divided into three parts. The first part reviews the appropriate fundamental concepts of logic and computability theory and can stand alone as an introduction to these topics. The second part discusses PDL and its variants, and the third part discusses DL and its variants. Examples are provided throughout, and exercises and a short historical section are included at the end of each chapter.

Dynamic Logic

We suggest a new simple forwarding technique to speed-up IP destination address lookup. The technique is a natural extension of IP, requires 5 bits in the IP header (IPv4, 7 in IPv6) and performs IP lookup nearly as fast as IP/Tag-switching but with a smaller memory requirement and a much simpler protocol. The basic idea is that each router adds a "clue" to each packet, telling its downstream router where it ended the IP lookup. Since the forwarding tables of neighboring routers are similar, the clue either directly determines the best prefix match for the downstream router, or provides the downstream router with a good point to start its IP lookup. The new scheme thus prevents repeated computations and distributes the lookup process across the routers along the packet path. Each router starts the lookup computation at the point its up-stream neighbor has finished. Furthermore, the new scheme is easily assimilated into heterogeneous IP networks, does not require routers coordination, and requires no setup time. Even a flow of one packet enjoys the benefits of the scheme without any additional overhead. The speedup we achieve is about 10 times faster than current standard techniques. In a sense this paper shows that the current routers employed in the Internet are clue-less; Namely, it is possible to speedup the IP-lookup by an order of magnitude without any major changes to the existing protocols.

https://www.faculty.idc.ac.il/bremler/Papers/RoutingJournal.pdf

Routing with a clue

Poor placement of data blocks in memory may negatively impact application performance because of an increase in the cache conflict miss rate [18]. For dynamically allocated structures this placement is typically determined by the memory allocator. Cache index-oblivious allocators may inadvertently place blocks on a restricted fraction of the available cache indexes, artificially and needlessly increasing the conflict miss rate. While some allocators are less vulnerable to this phenomena, no general-purpose malloc allocator is index-aware and methodologically addresses this concern. We demonstrate that many existing state-of-the-art allocators are index-oblivious, admitting performance pathologies for certain block sizes. We show that a simple adjustment within the allocator to control the spacing of blocks can provide better index coverage, which in turn reduces the superfluous conflict miss rate in various applications, improving performance with no observed negative consequences. The result is an index-aware allocator. Our technique is general and can easily be applied to most memory allocators and to various processor architectures.Furthermore, we can reduce inter-thread and inter-process conflict misses for processors where threads concurrently share the level-1 cache such as the Sun UltraSPARC-T2™ and Intel "Nehalem" by coloring the placement of blocks so that allocations for different threads and processes start on different cache indexes.

Cache index-aware memory allocation

A method for multiplexing the buffer space used to store messages of backlogged flows at the output port of a switch. The buffer space is partitioned among queues of variable length, with the first queue long enough to accommodate the largest expected backlog, the second queue long enough to accommodate the second-largest expected backlog, etc. Messages are dequeued from the queues for transmission in Round-Robin order. Incoming messages are enqueued in a manner that guarantees that messages of heavily backlogged flows tend to be enqueued in the longer queues, while preserving FIFO message order. If the messages are all of the same length, then the queues are partitioned into locations, of the same length as the messages, each location having an ordinal index in its queue, and the messages are enqueued so that each message of a particular flow is enqueued in a location with a different ordinal index. If the messages are of different lengths, the queues are partitioned into bins large enough to accommodate the longest messages, one or more messages may be stored in each bin, the round in which each incoming message is to be transmitted is computed in advance, and a similar enqueueing algorithm is used that is based on matching successive transmission rounds of messages of a given flow to successively indexed bins of different queues. The present invention may be used in any application involving Round Robin scheduling.

Space efficient fair queuing by stochastic Memory multiplexing

Read-write locks are one of the most prevalent lock forms in concurrent applications because they allow read accesses to locked code to proceed in parallel. However, they do not offer any parallelism between reads and writes.

This paper introduces pessimistic lock-elision (PLE), a new approach for non-speculatively replacing read-write locks with pessimistic (i.e. non-aborting) software transactional code that allows read-write concurrency even for contended code and even if the code includes system calls. On systems with hardware transactional support, PLE will allow failed transactions, or ones that contain system calls, to preserve read-write concurrency.

Our PLE algorithm is based on a novel encounter-order design of a fully pessimistic STM system that in a variety of benchmarks spanning from counters to trees, even when up to 40% of calls are mutating the locked structure, provides up to 5 times the performance of a state-of-the-art read-write lock.

Pessimistic Software Lock-Elision

It was recently shown that no data link protocol with finite sequence-numbers and deterministic finite state transmitter and receiver can tolerate transmitter and/or receiver crashes and recoveries, unless they have a non-volatile memory. Furthermore, it was proved that no self-stabilizing data link protocol in such a model exists. In this note we relax these assumptions and present two simple self-stabilizing data link protocols that use three sequence-numbers, and do not resort to non-volatile memory. The first is a randomized protocol (i.e., relaxing the deterministic transmitter and/or receiver assumption), and the second is a deterministic protocol that requires the transmitter to generate an infinite, a periodic sequence of sequence-numbers (i.e., relaxing the finite-state assumptions).

http://ieeexplore.ieee.org/iel4/5787/15446/00720145.pdf

Yehuda Afek

Papers

Routing with a clue

Cache index-aware memory allocation

Space efficient fair queuing by stochastic Memory multiplexing

Pessimistic Software Lock-Elision

Self-Stabilization of the Alternating-Bit Protocol