The proceedings contain 21 papers. The topics discussed include: enhancing the performance of photonic crystal and gates with machine learning optimization;bitcoin price prediction based on financial data, technical i...
ISBN:
(纸本)9798350381580
The proceedings contain 21 papers. The topics discussed include: enhancing the performance of photonic crystal and gates with machine learning optimization;bitcoin price prediction based on financial data, technical indicators, and news headlines sentiment analysis using CNN and GRU deep learning algorithms;promoting cybersecurity knowledge via gamification: an innovative intervention design;modeling and verification of the causal broadcast algorithm using colored Petri Nets;GPU-based parallel technique for solving n-similarity problem in textual data mining;a novel approach for specification and verification of symmetric distributed algorithms using spin;optimizing geophysical workloads in high-performance computing: leveraging machine learning and transformer models for enhanced parallelism and processor allocation;and rational Jacobi kernel functions: a novel massively parallelizable orthogonal kernel for support vector machines.
The emergence of new storage like persistent memory (PM) and zoned namespaces SSDs (ZNS-SSDs) introduces new challenges and opportunities for distributed key-value stores. Since LSM-tree has been widely adopted in dis...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
The emergence of new storage like persistent memory (PM) and zoned namespaces SSDs (ZNS-SSDs) introduces new challenges and opportunities for distributed key-value stores. Since LSM-tree has been widely adopted in distributed key-value stores, such as RocksDB and HBase, it is necessary to revisit the LSM-tree to make it adapt to new storage. In this paper, we first analyze the challenges of adapting the LSM-tree for new storage. Then, we propose a high-level architecture for a new-storage-aware LSM-tree-based key-value store called Hybrid-LSM. We explain the key structural issues of different storage layers in Hybrid-LSM and present some preliminary design ideas.
In this paper, we highlight and quantify the importance and potential role of In-Memory Computation (IMC) and memory technologies in the future of humans' global footprint. To this end, we calculate the estimated ...
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ISBN:
(纸本)9798350386257;9798350386240
In this paper, we highlight and quantify the importance and potential role of In-Memory Computation (IMC) and memory technologies in the future of humans' global footprint. To this end, we calculate the estimated energy consumption and carbon emission associated with the data movement inside computingsystems and put them in perspective using tangible examples. Next, we review various memory technologies as well as their advantages and disadvantages (especially regarding their energy consumption), for usage in computingsystems as memory and computing elements. We calculate what their impact is and what would be the potential savings of migrating towards emerging memory technologies. We discuss some of the challenges these emerging memory technologies face, before presenting the highlights of the IMC products on or near the market. This paper aims at providing an insight on the impact of IMC and memory technology on the society at large and clarify the importance of working on IMC and emerging memory technologies to lower the power consumption and overall footprint of computingsystems. The status of IMC products show that while moving in the right direction, there is a substantial body of work to be done. We hope this will help engineers to better grasp the extent of the impact they can produce and motivate them further in the pursuit of better computingsystems.
Asynchronous agreement protocols are crucial in various emerging applications, spanning from blockchains to fault-tolerant cyber-physical systems. Present asynchronous agreement protocols employ either randomization, ...
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ISBN:
(纸本)9798350395716;9798350395709
Asynchronous agreement protocols are crucial in various emerging applications, spanning from blockchains to fault-tolerant cyber-physical systems. Present asynchronous agreement protocols employ either randomization, incurring substantial computation overhead, or approximate agreement techniques, leading to high (O) over tilde (n(3)) communication for an n-node system. We address this inefficiency of approximate agreement protocols in the context of two different applications: a) Convex Agreement for distributed Oracles, and b) Asynchronous random beacons, by proposing two protocols titled DELPHI and HASHRAND, respectively.
The rapid development of quantum computing technology has opened new possibilities for solving complex problems beyond the capabilities of classical computing paradigms. However, combining quantum computing with class...
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ISBN:
(纸本)9798350368482;9798350368475
The rapid development of quantum computing technology has opened new possibilities for solving complex problems beyond the capabilities of classical computing paradigms. However, combining quantum computing with classical systems to create Hybrid Quantum-Classical (HQC) software systems presents unique challenges that require novel approaches in software architecture. This paper proposes a foundation for developing Architecture Description Languages (ADLs) specifically for HQC systems. We aim to provide a robust framework for coherently describing, integrating, and analyzing quantum and classical computing elements. The paper discusses the design principles, methodology, and structural components of the architecture description languages and outlines future research directions.
Traffic measurement is key to many important network functions. Supporting real-time queries at the individual flow level over networkwide traffic represents a major challenge that has not been successfully addressed ...
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ISBN:
(数字)9781665471770
ISBN:
(纸本)9781665471770
Traffic measurement is key to many important network functions. Supporting real-time queries at the individual flow level over networkwide traffic represents a major challenge that has not been successfully addressed yet. This paper provides the first solutions in supporting real-time networkwide queries and allowing a local network function (for performance, security or management purpose) to make queries at any measurement point at any time on any flow's networkwide statistics, while the packets of the flow may traverse different paths in the network, some of which may not come across the point where the query is made. Our trace-based experiments demonstrate that the proposed solutions significantly outperform the baseline solutions derived from the existing techniques.
The particle Markov-chain Monte Carlo (PMCMC) method is a stochastic algorithm that combines Particle Filters (PFs) and Markov-chain Monte Carlo (MCMC) techniques. This approach is widely used in Bayesian inference fo...
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ISBN:
(纸本)9798350350920
The particle Markov-chain Monte Carlo (PMCMC) method is a stochastic algorithm that combines Particle Filters (PFs) and Markov-chain Monte Carlo (MCMC) techniques. This approach is widely used in Bayesian inference for high-dimensional state spaces and nonlinear, non-Gaussian dynamic systems. However, current PMCMC accelerators face significant challenges due to their intensive computational complexity and the intricate particle routing, limiting their application in real-time scenarios. To address these challenges, we propose a novel distributed PMCMC method that leverages parallel computing to enhance hardware execution speed. Additionally, our method introduces a particle exchange scheme that not only resolves the accuracy issues caused by particle routing in distributed PMCMC but also achieves faster computing speed. Our design is implemented on a Xilinx Kintex-7 xc7k480t FPGA device. Experimental results demonstrate that our accelerator is nearly 65x faster than CPU performance, and provides speedups up to 5x compared to existing FPGA-based accelerators.
Direct memory access (RDMA) over Converged Ethernet (RoCE) allows for direct memory transfers between systems, granting minimal latency and CPU overhead. This allows low-latency applications where data collection, ana...
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ISBN:
(纸本)9798350377330;9798350377323
Direct memory access (RDMA) over Converged Ethernet (RoCE) allows for direct memory transfers between systems, granting minimal latency and CPU overhead. This allows low-latency applications where data collection, analytics and feedback to the user are distributed between different nodes, optimizing resource management. RoCE, originally designed for data center operations, has the potential to effectively support applications deployed on edge nodes, where limited resources are available and low latency is required. This demo shows the use of RoCE in support to an AI-based application for smart shopping, deployed at the edge.
Electricity load calculation of high-speed train group is one critical step for traction power system design. The energy-saving oriented electricity load calculation of high-speed train group is time-consuming. A dist...
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A novel distributedcomputing model called Multiaccess distributedcomputing (MADC) was recently introduced in [B. Federico and P. Elia, "Multi-Access distributedcomputing," June 2022, [online] Available: h...
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ISBN:
(纸本)9798350382853;9798350382846
A novel distributedcomputing model called Multiaccess distributedcomputing (MADC) was recently introduced in [B. Federico and P. Elia, "Multi-Access distributedcomputing," June 2022, [online] Available: http://***:2206.12851]. The MADC models with Combinatorial Topology (CT) were studied, where there are Lambda mapper nodes and K = ((Lambda)(alpha)) reducer nodes with each reducer node connected to distinct ff mapper nodes. In this paper, we represent MADC models via 2-layered bipartite graphs called Map-Reduce Graphs (MRGs), and a set of arrays called Map-Reduce Arrays (MRAs) inspired from the Placement Delivery Arrays (PDAs) used in the coded caching literature. The connection between MRAs and MRGs is established, thereby providing coded shuffling schemes for the MADC models using the structure of MRAs. Moreover, a set of gregular MRAs is provided which corresponds to the existing scheme for MADC models with CT. One of the major limitations of the existing scheme for CT is that it requires an exponentially large number of reducer nodes for large Lambda. This can be overcome by representing CT by MRAs, where coding schemes can be derived even if some of the reducer nodes are not present.
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