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Key-value (KV) stores based on the LSM tree have become a foundational layer in the storage stack of datacenters and cloud services. Current approaches for achieving reliability and availability favor reducing network traffic and send to replicas only new KV pairs. As a result, they perform costly compactions to reorganize data in both the primary and backup nodes, which increases device I/O traffic and CPU overhead, and eventually hurts overall system performance. In this article, we describe Tebis, an efficient LSM-based KV store that reduces I/O amplification and CPU overhead for maintaining the replica index. We use a primary-backup replication scheme that performs compactions only on the primary nodes and sends pre-built indexes to backup nodes, avoiding all compactions in backup nodes. Our approach includes an efficient mechanism to deal with pointer translation across nodes in the pre-built region index. Our results show that Tebis reduces resource utilization on backup nodes compared to performing full compactions: throughput is increased by 1.06 to 2.90×, CPU efficiency is increased by 1.21 to 2.78×, and I/O amplification is reduced by 1.7 to 3.27×, whereas network traffic increases by up to 1.32 to 3.76x. [ABSTRACT FROM AUTHOR]

VI-attached database storage architecture is presented to improve database transaction rates. In particular, the way VI-based interconnects could be used to improve I/O path performance between a database server and a storage subsystem is examined.

Persistent key-value stores have emerged as a main component in the data access path of modern data processing systems. However, they exhibit high CPU and I/O overhead. Nowadays, due to power limitations, it is important to reduce CPU overheads for data processing. In this article, we propose Kreon, a key-value store that targets servers with flash-based storage, where CPU overhead and I/O amplification are more significant bottlenecks compared to I/O randomness. We first observe that two significant sources of overhead in key-value stores are: (a) The use of compaction in Log-Structured Merge-Trees (LSM-Tree) that constantly perform merging and sorting of large data segments and (b) the use of an I/O cache to access devices, which incurs overhead even for data that reside in memory. To avoid these, Kreon performs data movement from level to level by using partial reorganization instead of full data reorganization via the use of a full index per-level. Kreon uses memory-mapped I/O via a custom kernel path to avoid a user-space cache. For a large dataset, Kreon reduces CPU cycles/op by up to 5.8×, reduces I/O amplification for inserts by up to 4.61×, and increases insert ops/s by up to 5.3×, compared to RocksDB. [ABSTRACT FROM AUTHOR]

This volume presents selected papers of young scientists – participants of International Young Scientists Conference in Computational Science (YSC'2020). This annual event has been annually organized by ITMO University since 2012 and aims to develop a dialogue about the present and the future of computational science with a focus on applications of modeling and simulation to solve a wide range of problems in science, industry, and business. In this editorial we present retrospective analysis of scientific topics, which were presented during the YSC editions, and determine key trends of the conference, related to the interaction of computational and intelligent technologies. [ABSTRACT FROM AUTHOR]

1. INTRODUCTION As clusters of workstations, PCs, or symmetric multiprocessors (SMPs) become important platforms for parallel computing, there is increasing interest in supporting the attractive, shared-address-space (SAS) programming model across […], Clusters of symmetric multiprocessors (SMPs) are important platforms for high-performance computing. With the success of hardware cache-coherent distributed shared memory (DSM), a lot of effort has also been made to support the coherent shared-address-space programming model in software on clusters. Much research has been done in fast communication on clusters and in protocols for supporting software shared memory across them. However, the performance of software virtual memory (SVM) is still far from that achieved on hardware DSM systems. The goal of this paper is to improve the performance of SVM on system area network clusters by considering communication and protocol layer interactions. We first examine what are the important communication system bottlenecks that stand in the way of improving parallel performance of SVM clusters; in particular, which parameters of the communication architecture are most important to improve further relative to processor speed, which ones are already adequate on modern systems for most applications, and how will this change with technology in the future. We find that the most important communication subsystem cost to improve is the overhead of generating and delivering interrupts for asynchronous protocol processing. Then we proceed to show, that by providing simple and general support for asynchronous message handling in a commodity network interface (NI) and by altering SVM protocols appropriately, protocol activity can be decoupled from asynchronous message handling, and the need for interrupts or polling can be eliminated. The NI mechanisms needed are generic, not SVM-dependent. We prototype the mechanisms and such a synchronous home-based LRC protocol, called GeNIMA (GEneral-purpose Network Interface support for shared Memory Abstractions), on a cluster of SMPs with a programmable NI. We find that the performance improvements are substantial, bringing performance on a small-scale SMP cluster much closer to that of hardware-coherent shared memory for many applications, and we show the value of each of the mechanisms in different applications.

Abstract This volume presents the selected papers of young computational scientists – participants of YSC'2018. Annual Young Scientist Conferences (YSC) in computational science are traditionally held since 2012 by the University of Amsterdam (the Netherlands) and ITMO University (St. Petersburg, Russia) as the open international event, which aim to develop a dialogue about the present and future of computational science with a focus on applications of modeling and simulation solving a wide range of problems of science, industry, and business. [ABSTRACT FROM AUTHOR]

We present DRASync, a region-based allocator that implements a global address space abstraction for MPI programs with pointer-based data structures. The main features of DRASync are: (a) it amortizes communication among nodes to allow efficient parallel allocation in a global address space; (b) it takes advantage of bulk deallocation and good locality with pointer-based data structures; (c) it supports ownership semantics of regions by nodes akin to reader–writer locks, which makes for a high-level, intuitive synchronization tool in MPI programs, without sacrificing message-passing performance. We evaluate DRASync against a state-of-the-art distributed allocator and find that it produces comparable performance while offering a higher-level abstraction to programmers. [ABSTRACT FROM PUBLISHER]

Novel eHealth systems are being designed to provide a citizen-centered health system, however the even demanding need for computing and data resources has required the adoption of Grid technologies. In most of the cases, this novel Health Grid requires not only conveying patient's personal data through public networks, but also storing it into shared resources out of the hospital premises. These features introduce new security concerns, in particular related with privacy. In this paper we survey current legal and technological approaches that have been taken to protect a patient's personal data into eHealth systems, with a particular focus in Intensive Care Grids. However, thanks to a security analysis applied over the Intensive Care Grid system (ICGrid) we show that these security mechanisms are not enough to provide a comprehensive solution, mainly because the data-at-rest is still vulnerable to attacks coming from untrusted Storage Elements where an attacker may directly access them. To cope with these issues, we propose a new privacy-oriented protocol which uses a combination of encryption and fragmentation to improve data's assurance while keeping compatibility with current legislations and Health Grid security mechanisms. [ABSTRACT FROM AUTHOR]

This article presents a VI-attached database storage architecture to improve database transaction rates. More specifically, we examine how VI-based interconnects can be used to improve I/O path performance between a database server and a storage subsystem. To facilitate the interaction between client applications and a VI-aware storage system, we design and implement a software layer called DSA, that is layered between applications and VI. DSA takes advantage of specific VI features and deals with many of its shortcomings. We provide and evaluate one kernel-level and two user-level implementations of DSA. These implementations trade transparency and generality for performance at different degrees and, unlike research prototypes, are designed to be suitable for real-world deployment. We have also investigated many design trade offs in the storage cluster. We present detailed measurements using a commercial database management system with both microbenchmarks and industrial database workloads on a mid-size, 4 CPU, and a large, 32 CPU, database server. We also compare the effectiveness of Vl-attached storage with an iSCSI configuration, and conclude that storage protocols implemented using DSA over VI have significant performance advantages. More generally, our results show that VI-based interconnects and user-level communication can improve all aspects of the I/O path between the database system and the storage back-end. We also find that to make effective use of VI in I/O intensive environments, we need to provide substantial additional functionality than what is currently provided by VI. Finally, new storage APIs that help minimize kernel involvement in the I/O path are needed to fully exploit the benefits of VI-based communication. [ABSTRACT FROM AUTHOR]

Although the shared memory abstraction is gaining ground as a programming abstraction for parallel computing, the main platforms that support it, small-scale symmetric multiprocessors (SMPs) and hardware cache-coherent distributed shared memory systems (DSMs), seem to lie inherently at the extremes of the cost-performance spectrum for parallel systems. In this paper we examine if shared virtual memory (SVM) clusters can bridge this gap by examining how application performance scales on a state-of-the-art shared virtual memory cluster. We find that: (i) The level of application restructuring needed is quite high compared to applications that perform well on a DSM system of the same scale and larger problem sizes are needed for good performance. (ii) However, surprisingly, SVM performs quite well for a fairly wide range of applications, achieving at least half the parallel efficiency of a high-end DSM system at the same scale and often much more. [Copyright &y& Elsevier]

This volume presents selected papers of young computational scientists – participants of YSC'2019. Annual Young Scientists Conferences in computational science are traditionally held since 2012 by the University of Amsterdam (the Netherlands) and ITMO University (St. Petersburg, Russia) as an event, which aims to develop a dialogue about the present and future of computational science with a focus on applications of modeling and simulation to solve a wide range of problems in science, industry, and business. [ABSTRACT FROM AUTHOR]

This article evaluates the scalability and productivity of six parallel programming models for heterogeneous architectures, and finds that task-based models using code and data annotations require the minimum programming effort while sustaining nearly best performance. However, achieving this result requires both extensions of programming models to control locality and granularity and proper interoperability with platform-specific optimizations. [ABSTRACT FROM PUBLISHER]

Abstract: High-performance storage systems are evolving towards decentralized commodity clusters that can scale in capacity, processing power, and network throughput. Building such systems requires: (a) Sharing physical resources among applications; (b) Sharing data among applications; (c) Allowing customized data views. Current solutions typically satisfy the first two requirements through a cluster file-system, resulting in monolithic, hard-to-manage systems. In this paper we present a storage system that addresses all three requirements by extending the block layer below the file-system. First, we discuss how our system provides customized (virtualized) storage views within a single node. Then, we discuss how it scales in clustered setups. To achieve efficient resource and data sharing we support block-level allocation and locking as in-band mechanisms. We implement a prototype under Linux and use it to build a shared cluster file-system. Our evaluation in a 24-node cluster setup concludes that our approach offers flexibility, scalability and reduced effort to implement new functionality. [Copyright &y& Elsevier]

Novel eHealth systems are being designed to provide a citizen-centered health system, however the even demanding need for computing and data resources has required the adoption of Grid technologies. In most of the cases, this novel Health Grid requires not only conveying patient's personal data through public networks, but also storing it into shared resources out of the hospital premises. These features introduce new security concerns, in particular related with privacy. In this paper we survey current legal and technological approaches that have been taken to protect a patient's personal data into eHealth systems, with a particular focus in Intensive Care Grids. However, thanks to a security analysis applied over the Intensive Care Grid system (ICGrid) we show that these security mechanisms are not enough to provide a comprehensive solution, mainly because the data-at-rest is still vulnerable to attacks coming from untrusted Storage Elements where an attacker may directly access them. To cope with these issues, we propose a new privacy-oriented protocol which uses a combination of encryption and fragmentation to improve data's assurance while keeping compatibility with current legislations and Health Grid security mechanisms.