Computability: Exploring Theoretical Limits of Computation
Delve into computability theory, focusing on what is computable and the limits of computation. Explore concepts like Rice's Theorem, the Halting Problem, and classes of expressiveness in computability theory, such as combinational logic, finite-state machines, pushdown automata, and Turing machines.
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Overview of Distributed Systems: Characteristics, Classification, Computation, Communication, and Fault Models
Characterizing Distributed Systems: Multiple autonomous computers with CPUs, memory, storage, and I/O paths, interconnected geographically, shared state, global invariants. Classifying Distributed Systems: Based on synchrony, communication medium, fault models like crash and Byzantine failures. Comp
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Overview of Distributed Operating Systems
Distributed Operating Systems (DOS) manage computer resources and provide users with convenient interfaces. Unlike centralized systems, DOS runs on multiple independent CPUs and prioritizes software over hardware. It ensures transparency and fault tolerance, with a focus on software error handling.
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Understanding CS 394B: Blockchain Systems and Distributed Consensus
This course, led by Assistant Professor Marco Canini, delves into the technical aspects of blockchain technologies, distributed consensus, and secure software engineering. Students will engage in flipped classroom-style classes and paper presentations, critiquing research papers, defending research
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Understanding Distributed Mutual Exclusion in Operating Systems
In distributed systems, the problem of mutual exclusion arises when multiple sites/processes need to access shared resources concurrently. Unlike in single-computer systems, distributed systems lack shared memory, leading to the need for communication-based approaches rather than shared variables li
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Understanding Parallel and Distributed Computing Systems
In parallel computing, processing elements collaborate to solve problems, while distributed systems appear as a single coherent system to users, made up of independent computers. Contemporary computing systems like mobile devices, IoT devices, and high-end gaming computers incorporate parallel and d
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Designing Distributed and Internet Systems
Learn about the design considerations for distributed and internet systems, including file server versus client/server environments, cloud computing trends, internet standards, and system development life cycle. Explore designing systems for local area networks (LANs) and the process of creating dis
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Computation of Machine Hour Rate: Understanding MHR and Overhead Rates
Computation of Machine Hour Rate (MHR) involves determining the overhead cost of running a machine for one hour. The process includes dividing overheads into fixed and variable categories, calculating fixed overhead hourly rates, computing variable overhead rates, and summing up both for the final M
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Enhanced Security in Multiparty Computation
Explore the improved black-box constructions of composable secure computation, focusing on definitions, objectives, and the formalization basics of multiparty computation (MPC). Learn about the motivating security aspects in MPC and the real/ideal paradigm. Discover how MPC security involves compari
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High-Level Thoughts on Distributed Tone Resource Unit (dRU) Design in IEEE 802.11-23/1988r2 November 2023
Various aspects of Distributed Tone Resource Unit (dRU) design in IEEE 802.11-23/1988r2, such as PSD limitations, distributed transmission regulations, application areas, and open questions are discussed in this presentation by Lin Yang from Qualcomm. Topics include tone distribution, power pooling
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Understanding Remote Method Invocation (RMI) in Distributed Systems
A distributed system involves software components on different computers communicating through message passing to achieve common goals. Organized with middleware like RMI, it allows for interactions across heterogeneous networks. RMI facilitates building distributed Java systems by enabling method i
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Understanding Remote Method Invocation (RMI) in Distributed Systems
A distributed system involves components on different computers communicating to achieve a common goal. Middleware, like RMI, helps organize these systems. RMI allows Java objects to invoke methods on remote objects, facilitating distributed Java systems. It differs from RPC by focusing on object-or
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Understanding Parallel and Distributed Systems in Computing
A parallel computer is a collection of processing elements that collaborate to solve problems, while a distributed system comprises independent computers appearing as a single system. Contemporary computing systems, like mobile devices and cloud platforms, utilize parallel and distributed architectu
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Understanding Numerical Methods and Errors in Computation
Delve into the world of numerical methods through the guidance of Dr. M. Mohamed Surputheen. Explore topics such as solving algebraic and transcendental equations, simultaneous linear algebraic equations, interpolation, numerical integration, and solving ordinary differential equations. Learn about
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Understanding Message Passing in Distributed Systems
Explore the key concepts of message passing in distributed systems, covering inter-process communication, desirable features like simplicity, efficiency, and reliability, different methods for information sharing, and the importance of synchronization and buffering. Dive into the intricacies of enco
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Distributed DBMS Reliability Concepts and Measures
Distributed DBMS reliability is crucial for ensuring continuous user request processing despite system failures. This chapter delves into fundamental definitions, fault classifications, and types of faults like hard and soft failures in distributed systems. Understanding reliability concepts helps i
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SmartNIC Offloading for Distributed Applications
This presentation discusses offloading distributed applications onto SmartNICs using the iPipe framework. It explores the potential of programmable NICs to accelerate general distributed applications, characterizes multicore SmartNICs, and outlines the development and evaluation process. The study c
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Secure Computation Techniques in RAM Models with Efficient Automation
Explore the automation of efficient RAM-model secure computation techniques, including examples such as secure binary search. Discover how traditional solutions using circuit abstractions can be improved for sub-linear time computation through methods like Oblivious RAM. Learn about techniques such
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Secure Multiparty Computation for Department of Education Data Sharing
This report discusses the use of Secure Multiparty Computation (SMC) to enable sharing of sensitive Department of Education data across organizational boundaries. The application of SMC allows for joint computation while keeping individual data encrypted, ensuring privacy and security within the Nat
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Advancements in Active Secure Multiparty Computation (MPC)
Delve into the realm of secure multiparty computation under 1-bit leakage, exploring the intersection of DP algorithms, MPC, and the utilization of leakage for enhanced performance. Discover the overhead implications of achieving active security, as well as the evolution of secure computation protoc
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Understanding Causal Consistency in Distributed Systems
This content covers the concept of causal consistency in computing systems, exploring consistency models such as Causal Linearizability and Eventual Sequential. It explains the importance of logical clocks like Lamport and vector clocks, and how they ensure order in distributed systems. The concept
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Enhancing IoT Systems with Blockchain and Distributed Ledger Technologies
Explore the potential of blockchain and distributed ledger technologies in enhancing IoT systems, focusing on privacy, security, and safety. The workshop discusses the benefits and challenges of implementing DLT, as well as a reference IoT scenario in the manufacturing industry. Discover how DLT ena
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Overview of Mutual Exclusion and Memory Models in Distributed Systems
Discussion on fast, randomized mutual exclusion techniques by George Giakkoupis and Philipp Woelfel. Exploring asynchronous shared memory systems with atomic operations. Understanding mutual exclusion principles as outlined by Dijkstra in 1965 and measuring time efficiency in critical sections. Delv
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Secure Multiparty Computation: Enhancing Privacy in Data Sharing
Secure multiparty computation (SMC) enables parties with private inputs to compute joint functions without revealing individual data, ensuring privacy and correctness. This involves computations on encrypted data using techniques like homomorphic encryption for scenarios like e-voting. SMC serves as
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Economic Models of Consensus on Distributed Ledgers in Blockchain Technology
This study delves into Byzantine Fault Tolerance (BFT) protocols in the realm of distributed ledgers, exploring the complexities of achieving consensus in trusted adversarial environments. The research examines the classic problem in computer science where distributed nodes communicate to reach agre
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Distributed Consensus Models in Blockchain Networks
Economic and technical aspects of Byzantine Fault Tolerance (BFT) protocols for achieving consensus in distributed ledger systems are explored. The discussion delves into the challenges of maintaining trust in adversarial environments and the strategies employed by non-Byzantine nodes to mitigate un
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Distributed Algorithms for Leader Election in Anonymous Systems
Distributed algorithms play a crucial role in leader election within anonymous systems where nodes lack unique identifiers. The content discusses the challenges and impossibility results of deterministic leader election in such systems. It explains synchronous and asynchronous distributed algorithms
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COMET: Code Offload by Migrating Execution - OSDI'12 Summary
The research paper discusses COMET, a system for transparently offloading computation from mobile devices to network resources to improve performance. It outlines the goals of COMET, its design, and evaluation, focusing on distributed shared memory and bridging computation disparity through offloadi
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Actively Secure Arithmetic Computation and VOLE Study
Exploring actively secure arithmetic computation and VOLE with constant computational overhead at Tel Aviv University. Understanding how functions are represented in secure computation using arithmetic circuits over boolean circuits. Efficiently evaluating arithmetic circuits over large finite field
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Distributed Graph Algorithms: Introduction and Tree Coloring
This class introduces the fundamentals of distributed graph algorithms focusing on network modeling, complexity measures, solving graph problems, and comparing distributed vs. centralized algorithms. It covers topics such as the LOCAL model, synchronous rounds, communication rounds, computation time
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Enhancing Multi-Party Computation Efficiency Through ORAM Techniques
Explore the realm of efficient random access in multi-party computation through the reevaluation of classic schemes and the introduction of new approaches. Discover the potential of ORAM in improving performance and reducing costs in various computational tasks, such as secure multi-party computatio
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Distributed Biconnectivity in Graph Analysis for Efficient Network Solutions
Graph biconnectivity is a crucial concept in network analysis, ensuring connectivity even when vertices are removed. Efficient distributed biconnectivity algorithms have practical applications in identifying single points of failure in networks. Leveraging previous work on Ice Sheet Connectivity, a
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Introduction to TensorFlow: A Comprehensive Overview
TensorFlow, a popular open-source machine learning framework, offers various execution modes including graph and eager execution. It provides benefits such as distributed training and performance optimizations. The architecture involves assembling computational graphs and executing operations using
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Challenges of Time Synchronization in Distributed Systems
Distributed systems face challenges in synchronizing physical time due to varying network paths and clock drifts. While physical time synchronization is useful for tasks like file timestamps, it involves complexities such as estimating communication latency and improving time estimation algorithms l
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Distributed Graph Coloring on Multiple GPUs: Advancements in Parallel Computation
This research introduces a groundbreaking distributed memory multi-GPU graph coloring implementation, achieving significant speedups and minimal color increase. The approach enables efficient coloring of large-scale graphs with billions of vertices and edges. Additionally, the study explores the pra
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Efficient Multi-Party Computation Techniques
Explore the innovative approaches to Multi-Party Computation (MPC) such as MPC via Fully Homomorphic Encryption (FHE) and Multi-Key FHE. The focus is on minimizing round complexity and achieving secure distributed computations. Learn about key concepts, protocols, and advancements in the realm of MP
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Understanding the Chubby Lock Service for Distributed Systems
The Chubby Lock Service, based on the research by Mike Burrows from Google, provides a mechanism for synchronizing activities in loosely-coupled distributed systems. It allows clients to agree on basic information, such as choosing a leader, with the help of advisory locks and event notifications. T
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Understanding MapReduce System and Theory in CS 345D
Explore the fundamentals of MapReduce in this informative presentation that covers the history, challenges, and benefits of distributed systems like MapReduce/Hadoop, Pig, and Hive. Learn about the lower bounding communication cost model and how it optimizes algorithm for joins on MapReduce. Discove
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Overview of Distributed Systems, RAID, Lustre, MogileFS, and HDFS
Distributed systems encompass a range of technologies aimed at improving storage efficiency and reliability. This includes RAID (Redundant Array of Inexpensive Disks) strategies such as RAID levels, Lustre Linux Cluster for high-performance clusters, MogileFS for fast content delivery, and HDFS (Had
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Chi: A Scalable and Programmable Control Plane for Distributed Stream Processing
Distributed stream processing systems are increasingly crucial for various production use cases, such as real-time dashboards, machine learning, and interactive debugging. The challenges of handling large variability in production ingestion workloads and high-degree data skew in queries are addresse
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