20,636 research outputs found
The End of Slow Networks: It's Time for a Redesign
Next generation high-performance RDMA-capable networks will require a
fundamental rethinking of the design and architecture of modern distributed
DBMSs. These systems are commonly designed and optimized under the assumption
that the network is the bottleneck: the network is slow and "thin", and thus
needs to be avoided as much as possible. Yet this assumption no longer holds
true. With InfiniBand FDR 4x, the bandwidth available to transfer data across
network is in the same ballpark as the bandwidth of one memory channel, and it
increases even further with the most recent EDR standard. Moreover, with the
increasing advances of RDMA, the latency improves similarly fast. In this
paper, we first argue that the "old" distributed database design is not capable
of taking full advantage of the network. Second, we propose architectural
redesigns for OLTP, OLAP and advanced analytical frameworks to take better
advantage of the improved bandwidth, latency and RDMA capabilities. Finally,
for each of the workload categories, we show that remarkable performance
improvements can be achieved
Parallel Discrete Event Simulation with Erlang
Discrete Event Simulation (DES) is a widely used technique in which the state
of the simulator is updated by events happening at discrete points in time
(hence the name). DES is used to model and analyze many kinds of systems,
including computer architectures, communication networks, street traffic, and
others. Parallel and Distributed Simulation (PADS) aims at improving the
efficiency of DES by partitioning the simulation model across multiple
processing elements, in order to enabling larger and/or more detailed studies
to be carried out. The interest on PADS is increasing since the widespread
availability of multicore processors and affordable high performance computing
clusters. However, designing parallel simulation models requires considerable
expertise, the result being that PADS techniques are not as widespread as they
could be. In this paper we describe ErlangTW, a parallel simulation middleware
based on the Time Warp synchronization protocol. ErlangTW is entirely written
in Erlang, a concurrent, functional programming language specifically targeted
at building distributed systems. We argue that writing parallel simulation
models in Erlang is considerably easier than using conventional programming
languages. Moreover, ErlangTW allows simulation models to be executed either on
single-core, multicore and distributed computing architectures. We describe the
design and prototype implementation of ErlangTW, and report some preliminary
performance results on multicore and distributed architectures using the well
known PHOLD benchmark.Comment: Proceedings of ACM SIGPLAN Workshop on Functional High-Performance
Computing (FHPC 2012) in conjunction with ICFP 2012. ISBN: 978-1-4503-1577-
Parallelizing Windowed Stream Joins in a Shared-Nothing Cluster
The availability of large number of processing nodes in a parallel and
distributed computing environment enables sophisticated real time processing
over high speed data streams, as required by many emerging applications.
Sliding window stream joins are among the most important operators in a stream
processing system. In this paper, we consider the issue of parallelizing a
sliding window stream join operator over a shared nothing cluster. We propose a
framework, based on fixed or predefined communication pattern, to distribute
the join processing loads over the shared-nothing cluster. We consider various
overheads while scaling over a large number of nodes, and propose solution
methodologies to cope with the issues. We implement the algorithm over a
cluster using a message passing system, and present the experimental results
showing the effectiveness of the join processing algorithm.Comment: 11 page
- …