2,268 research outputs found
Argobots: A Lightweight Low-Level Threading and Tasking Framework
In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, either are too specific to applications or architectures or are not as powerful or flexible. In this paper, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by end users or high-level programming models. We describe the design, implementation, and performance characterization of Argobots and present integrations with three high-level models: OpenMP, MPI, and colocated I/O services. Evaluations show that (1) Argobots, while providing richer capabilities, is competitive with existing simpler generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency-hiding capabilities; and (4) I/O services with Argobots reduce interference with colocated applications while achieving performance competitive with that of a Pthreads approach
The "MIND" Scalable PIM Architecture
MIND (Memory, Intelligence, and Network Device) is an advanced parallel computer architecture for high performance computing and scalable embedded processing. It is a
Processor-in-Memory (PIM) architecture integrating both DRAM bit cells and CMOS logic devices on the same silicon die. MIND is multicore with multiple memory/processor nodes on
each chip and supports global shared memory across systems of MIND components. MIND is distinguished from other PIM architectures in that it incorporates mechanisms for efficient support of a global parallel execution model based on the semantics of message-driven multithreaded split-transaction processing. MIND is designed to operate either in conjunction with other conventional microprocessors or in standalone arrays of like devices. It also incorporates mechanisms for fault tolerance, real time execution, and active power management. This paper describes the major elements and operational methods of the MIND
architecture
Performance Characterization of In-Memory Data Analytics on a Modern Cloud Server
In last decade, data analytics have rapidly progressed from traditional
disk-based processing to modern in-memory processing. However, little effort
has been devoted at enhancing performance at micro-architecture level. This
paper characterizes the performance of in-memory data analytics using Apache
Spark framework. We use a single node NUMA machine and identify the bottlenecks
hampering the scalability of workloads. We also quantify the inefficiencies at
micro-architecture level for various data analysis workloads. Through empirical
evaluation, we show that spark workloads do not scale linearly beyond twelve
threads, due to work time inflation and thread level load imbalance. Further,
at the micro-architecture level, we observe memory bound latency to be the
major cause of work time inflation.Comment: Accepted to The 5th IEEE International Conference on Big Data and
Cloud Computing (BDCloud 2015
R friendly multi-threading in C++
Calling multi-threaded C++ code from R has its perils. Since the R
interpreter is single-threaded, one must not check for user interruptions or
print to the R console from multiple threads. One can, however, synchronize
with R from the main thread. The R package RcppThread (current version 0.5.3)
contains a header only C++ library for thread safe communication with R that
exploits this fact. It includes C++ classes for threads, a thread pool, and
parallel loops that routinely synchronize with R. This article explains the
package's functionality and gives examples of its usage. The synchronization
mechanism may also apply to other threading frameworks. Benchmarks suggest
that, although synchronization causes overhead, the parallel abstractions of
RcppThread are competitive with other popular libraries in typical scenarios
encountered in statistical computing
Middleware-based Database Replication: The Gaps between Theory and Practice
The need for high availability and performance in data management systems has
been fueling a long running interest in database replication from both academia
and industry. However, academic groups often attack replication problems in
isolation, overlooking the need for completeness in their solutions, while
commercial teams take a holistic approach that often misses opportunities for
fundamental innovation. This has created over time a gap between academic
research and industrial practice.
This paper aims to characterize the gap along three axes: performance,
availability, and administration. We build on our own experience developing and
deploying replication systems in commercial and academic settings, as well as
on a large body of prior related work. We sift through representative examples
from the last decade of open-source, academic, and commercial database
replication systems and combine this material with case studies from real
systems deployed at Fortune 500 customers. We propose two agendas, one for
academic research and one for industrial R&D, which we believe can bridge the
gap within 5-10 years. This way, we hope to both motivate and help researchers
in making the theory and practice of middleware-based database replication more
relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on
Management of Data, Vancouver, Canada, June 200
A Survey on Wireless Sensor Network Security
Wireless sensor networks (WSNs) have recently attracted a lot of interest in
the research community due their wide range of applications. Due to distributed
nature of these networks and their deployment in remote areas, these networks
are vulnerable to numerous security threats that can adversely affect their
proper functioning. This problem is more critical if the network is deployed
for some mission-critical applications such as in a tactical battlefield.
Random failure of nodes is also very likely in real-life deployment scenarios.
Due to resource constraints in the sensor nodes, traditional security
mechanisms with large overhead of computation and communication are infeasible
in WSNs. Security in sensor networks is, therefore, a particularly challenging
task. This paper discusses the current state of the art in security mechanisms
for WSNs. Various types of attacks are discussed and their countermeasures
presented. A brief discussion on the future direction of research in WSN
security is also included.Comment: 24 pages, 4 figures, 2 table
Analysis of threading libraries for high performance computing
© 2020 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] With the appearance of multi-/many core machines, applications and runtime systems have evolved in order to exploit the new on-node concurrency brought by new software paradigms. POSIX threads (Pthreads) was widely-adopted for that purpose and it remains as the most used threading solution in current hardware. Lightweight thread (LWT) libraries emerged as an alternative offering lighter mechanisms to tackle the massive concurrency of current hardware. In this article, we analyze in detail the most representative threading libraries including Pthread- and LWT-based solutions. In addition, to examine the suitability of LWTs for different use cases, we develop a set of microbenchmarks consisting of OpenMP patterns commonly found in current parallel codes, and we compare the results using threading libraries and OpenMP implementations. Moreover, we study the semantics offered by threading libraries in order to expose the similarities among different LWT application programming interfaces and their advantages over Pthreads. This article exposes that LWT libraries outperform solutions based on operating system threads when tasks and nested parallelism are required.The researchers from the Universitat Jaume I and Universitat Politecnica de Valencia were supported by project TIN2014-53495-R of the MINECO and FEDER, and the Generalitat Valenciana fellowship programme Vali+d 2015. Antonio J. Pena is financed by the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant No. 749516. This work was partially supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research (SC-21), under contract DE-AC02-06CH11357.Castelló, A.; Mayo Gual, R.; Seo, S.; Balaji, P.; Quintana Ortí, ES.; Peña, AJ. (2020). Analysis of threading libraries for high performance computing. IEEE Transactions on Computers. 69(9):1279-1292. https://doi.org/10.1109/TC.2020.2970706S1279129269
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