We address fully-defective asynchronous networks, in which all links are subject to an unlimited number of alteration errors, implying that all messages in the network may be completely corrupted. Despite the possible...
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ISBN:
(纸本)9781450392624
We address fully-defective asynchronous networks, in which all links are subject to an unlimited number of alteration errors, implying that all messages in the network may be completely corrupted. Despite the possible intuition that such a setting is too harsh for any reliable communication, we show how to simulate any algorithm for a noiseless setting over any fully-defective setting, given that the network is 2-edge connected. We prove that if the network is not 2-edge connected, no non-trivial computation in the fully-defective setting is possible. The key structural property of 2-edge-connected graphs that we leverage is the existence of an oriented (non-simple) cycle that goes through all nodes [Robbins, 1939]. The core of our technical contribution is presenting a construction of such a Robbins cycle in fully-defective networks, and showing how to communicate over it despite total message corruption. These are obtained in a content-oblivious manner, since nodes must ignore the content of received messages.
distributedcomputing is at the heart of modern system architectures and infrastructures. But as security and privacy have increasingly become critical to every organization, modern cryptography is making its way into...
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ISBN:
(纸本)9781450392624
distributedcomputing is at the heart of modern system architectures and infrastructures. But as security and privacy have increasingly become critical to every organization, modern cryptography is making its way into core systems. In this talk, I will describe work that focuses on using modern cryptographic techniques in large scale practical distributed systems in order to improve their security and privacy guarantees. I will show how both cryptographic techniques and distributed systems need to be adapted to make this work and how to think about the security of these new encrypted distributed systems.
The national computing curriculum in Czechia was revised in 2021 to incorporate various topics, including fundamental principles of the internet and computer networks at the ISCED level 2 (age similar to 11-15). Howev...
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ISBN:
(纸本)9798400705311
The national computing curriculum in Czechia was revised in 2021 to incorporate various topics, including fundamental principles of the internet and computer networks at the ISCED level 2 (age similar to 11-15). However, schools face a shortage of age-appropriate teaching materials on this subject. To address this gap, we developed four model lessons and corresponding materials tailored for ISCED 2 students and teachers at two levels of difficulty. The primary objective of these lessons is to elucidate the structure and fundamental principles of the internet, building on prevalent student preconceptions. This work is grounded in the constructivist instructional framework known as Evocation - Realisation of Meaning Reflection (ERR). The lessons were created and validated through design-based research conducted across six schools, involving 13 classes and a total of approximately 270 students. Pre-post-delayed testing revealed very large immediate improvements following the intervention (d = 1.72, p < 0.001, n = 204) as well as large, sustained effects months later (d = 1.10, p < 0.001, n = 59). This paper details the development, implementation, and evaluation of these lessons, providing a valuable resource for educators in various contexts.
The proceedings contain 3 papers. The topics discussed include: cost-efficient construction of performance models;using benchmarking and regression models for predicting CNN training time on a GPU;and benchmarking mac...
ISBN:
(纸本)9798400706455
The proceedings contain 3 papers. The topics discussed include: cost-efficient construction of performance models;using benchmarking and regression models for predicting CNN training time on a GPU;and benchmarking machine learning applications on heterogeneous architecture using reframe.
The efficiency of distributed shared memory (DSM) has been greatly improved by recent hardware technologies. But, the difficulty of distributed memory management can still be a major obstacle to the democratization of...
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ISBN:
(纸本)9798400702297
The efficiency of distributed shared memory (DSM) has been greatly improved by recent hardware technologies. But, the difficulty of distributed memory management can still be a major obstacle to the democratization of DSM, especially when a partial failure of the participating clients (e.g., due to crashed processes or machines) should be tolerated. In this paper, we present CXL-SHM, an automatic distributed memory management system based on reference counting. The reference count maintenance in CXL-SHM is implemented with a special era-based non-blocking algorithm. Thus, there are no blocking synchronization, memory leak, double free, and wild pointer problems, even if some participating clients unexpectedly fail without freeing their possessed memory references. We evaluated our system on real CXL hardware with both micro-benchmarks and end-to-end applications, which demonstrate the efficiency of CXL-SHM and the simplicity/flexibility of using CXL-SHM to build efficient distributed applications.
distributed machine learning approaches, including a broad class of federated learning (FL) techniques, present a number of benefits when deploying machine learning applications over widely distributed infrastructures...
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ISBN:
(纸本)9798400703874
distributed machine learning approaches, including a broad class of federated learning (FL) techniques, present a number of benefits when deploying machine learning applications over widely distributed infrastructures. The benefits are highly dependent on the details of the underlying machine learning topology, which specifies the functionality executed by the participating nodes, their dependencies and interconnections. Current systems lack the flexibility and extensibility necessary to customize the topology of a machine learning deployment. We present Flame, a new system that provides flexibility of the topology configuration of distributed FL applications around the specifics of a particular deployment context, and is easily extensible to support new FL architectures. Flame achieves this via a new high-level abstraction Topology Abstraction Graphs (TAGs). TAGs decouple the ML application logic from the underlying deployment details, making it possible to specialize the application deployment with reduced development effort. Flame is released as an open source project, and its flexibility and extensibility support a variety of topologies and mechanisms, and can facilitate the development of new FL methodologies.
Bayesian Neural Networks (BNNs) offer a principled framework for modeling uncertainty in deep learning tasks. However, conventional BNNs often suffer from high computational complexity and parameter overhead. In this ...
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ISBN:
(纸本)9798400706059
Bayesian Neural Networks (BNNs) offer a principled framework for modeling uncertainty in deep learning tasks. However, conventional BNNs often suffer from high computational complexity and parameter overhead. In this paper, we propose a novel approach, termed Probabilistic BNN (ProbBNN), which leverages probabilistic computingprinciples to streamline the inference process. Unlike traditional deterministic approaches, ProbBNN represents inputs and parameters as random variables governed by probability distributions, allowing for the propagation of uncertainty throughout the network. We employ Gaussian Mixture Models (GMMs) to represent the parameters of each neuron or convolutional kernel, enabling efficient encoding and processing of uncertainty. Our approach simplifies the inference process by replacing complex deterministic computations with lightweight probabilistic operations, resulting in reduced computational complexity and improved scalability. Experimental results demonstrate the effectiveness of ProbBNN in achieving competitive accuracy to traditional BNNs while significantly reducing the number of parameters. The transition to ProbBNN yields a reduction of two orders of magnitude in the number of parameters compared to baseline approaches, making our approach promising for deployment in resource-constrained applications such as edge computing and IoT devices.
Intelligent Transportation Systems (ITS) involve integrating information and communication technologies with traffic infrastructure and vehicles to support the development of more sustainable transportation systems. H...
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ISBN:
(纸本)9798400703706
Intelligent Transportation Systems (ITS) involve integrating information and communication technologies with traffic infrastructure and vehicles to support the development of more sustainable transportation systems. However, ITS face security, reliability, and efficiency challenges in storage and sharing real-time critical data. To address these issues, we propose an architecture based on edge computing and blockchain to enable secure data storage and sharing for ITS. By leveraging edge computing capabilities and blockchain's distributed ledger technology, our architecture enhances data security, ensures data integrity, and improves real-time data processing in ITS. We analyze a smart parking system application scenario, and the results demonstrate a significant reduction in average latency and storage usage, highlighting the positive impact of our solution on enhancing the overall performance and reliability of ITS.
There is growing consensus that focused attention on increasing the computer science (CS) certification of Black and Brown teachers is needed. More certified CS Black and Brown teachers can propel equity-based CS prin...
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