uFLIP: Understanding Flash IO Patterns

Does the advent of flash devices constitute a radical change for secondary storage? How should database systems adapt to this new form of secondary storage? Before we can answer these questions, we need to fully understand the performance characteristics of flash devices. More specifically, we want to establish what kind of IOs should be favored (or avoided) when designing algorithms and architectures for flash-based systems. In this paper, we focus on flash IO patterns, that capture relevant distribution of IOs in time and space, and our goal is to quantify their performance. We define uFLIP, a benchmark for measuring the response time of flash IO patterns. We also present a benchmarking methodology which takes into account the particular characteristics of flash devices. Finally, we present the results obtained by measuring eleven flash devices, and derive a set of design hints that should drive the development of flash-based systems on current devices.Comment: CIDR 200

ViRMA: Virtual Reality Multimedia Analytics at LSC 2021

In this paper we describe the first iteration of the ViRMA prototype system, a novel approach to multimedia analysis in virtual reality and inspired by the M3 data model. We intend to evaluate our approach via the Lifelog Search Challenge (LSC) to serve as a benchmark against other multimedia analytics systems

Scalability of the NV-tree: Three Experiments

International audienceThe NV-tree is a scalable approximate high-dimensional indexing method specifically designed for large-scale visual instance search. In this paper, we report on three experiments designed to evaluate the performance of the NV-tree. Two of these experiments embed standard benchmarks within collections of up to 28.5 billion features, representing the largest single-server collection ever reported in the literature. The results show that indeed the NV-tree performs very well for visual instance search applications over large-scale collections

Elastic Collision Based Dynamic Partitioning Scheme for Hybrid Simulations

The scattering-adapted flexible inner region ensemble separator (SAFIRES) is a partitioning scheme designed to divide a simulation cell into two regions to be treated with different computational methodologies. SAFIRES prevents particles from crossing between regions and resolves boundary events through elastic collisions of the particles mediated by the boundary, conserving energy and momenta. A multiple-time-step propagation algorithm is introduced where the time step is scaled automatically to identify the moment a collision occurs. If the length of the time step is kept constant, the new propagator reduces to a regular algorithm for Langevin dynamics, and to the velocity Verlet algorithm for classical dynamics if the friction coefficient is set to zero. SAFIRES constitutes the exact limit of the premise behind boundary-based methods such as FIRES, BEST, and BCC which take advantage of the indistinguishability of molecules on opposite sides of the separator. It gives correct average ensemble statistics despite the introduction of an ensemble separator. SAFIRES is tested in simulations where the molecules on the two sides are treated in the same way, for a Lennard-Jones (LJ) liquid and a LJ liquid in contact with a surface, as well as for liquid modelling simulations using the TIP4P force field. Simulations using SAFIRES are shown to reproduce the unconstrained reference simulations without significant deviations.Comment: To be submitted to Journal of Chemical Theory and Computatio

Smart Contract Upgradeability on the Ethereum Blockchain Platform: An Exploratory Study

Context: Smart contracts are computerized self-executing contracts that contain clauses, which are enforced once certain conditions are met. Smart contracts are immutable by design and cannot be modified once deployed, which ensures trustlessness. Despite smart contracts' immutability benefits, upgrading contract code is still necessary for bug fixes and potential feature improvements. In the past few years, the smart contract community introduced several practices for upgrading smart contracts. Upgradeable contracts are smart contracts that exhibit these practices and are designed with upgradeability in mind. During the upgrade process, a new smart contract version is deployed with the desired modification, and subsequent user requests will be forwarded to the latest version (upgraded contract). Nevertheless, little is known about the characteristics of the upgrading practices, how developers apply them, and how upgrading impacts contract usage. Objectives: This paper aims to characterize smart contract upgrading patterns and analyze their prevalence based on the deployed contracts that exhibit these patterns. Furthermore, we intend to investigate the reasons why developers upgrade contracts (e.g., introduce features, fix vulnerabilities) and how upgrades affect the adoption and life span of a contract in practice. Method: We collect deployed smart contracts metadata and source codes to identify contracts that exhibit certain upgrade patterns (upgradeable contracts) based on a set of policies. Then we trace smart contract versions for each upgradable contract and identify the changes in contract versions using similarity and vulnerabilities detection tools. Finally, we plan to analyze the impact of upgrading on contract usage based on the number of transactions received and the lifetime of the contract version