44,615 research outputs found
The Impact of RDMA on Agreement
Remote Direct Memory Access (RDMA) is becoming widely available in data
centers. This technology allows a process to directly read and write the memory
of a remote host, with a mechanism to control access permissions. In this
paper, we study the fundamental power of these capabilities. We consider the
well-known problem of achieving consensus despite failures, and find that RDMA
can improve the inherent trade-off in distributed computing between failure
resilience and performance. Specifically, we show that RDMA allows algorithms
that simultaneously achieve high resilience and high performance, while
traditional algorithms had to choose one or another. With Byzantine failures,
we give an algorithm that only requires processes (where
is the maximum number of faulty processes) and decides in two (network)
delays in common executions. With crash failures, we give an algorithm that
only requires processes and also decides in two delays. Both
algorithms tolerate a minority of memory failures inherent to RDMA, and they
provide safety in asynchronous systems and liveness with standard additional
assumptions.Comment: Full version of PODC'19 paper, strengthened broadcast algorith
Revisiting Actor Programming in C++
The actor model of computation has gained significant popularity over the
last decade. Its high level of abstraction makes it appealing for concurrent
applications in parallel and distributed systems. However, designing a
real-world actor framework that subsumes full scalability, strong reliability,
and high resource efficiency requires many conceptual and algorithmic additives
to the original model.
In this paper, we report on designing and building CAF, the "C++ Actor
Framework". CAF targets at providing a concurrent and distributed native
environment for scaling up to very large, high-performance applications, and
equally well down to small constrained systems. We present the key
specifications and design concepts---in particular a message-transparent
architecture, type-safe message interfaces, and pattern matching
facilities---that make native actors a viable approach for many robust,
elastic, and highly distributed developments. We demonstrate the feasibility of
CAF in three scenarios: first for elastic, upscaling environments, second for
including heterogeneous hardware like GPGPUs, and third for distributed runtime
systems. Extensive performance evaluations indicate ideal runtime behaviour for
up to 64 cores at very low memory footprint, or in the presence of GPUs. In
these tests, CAF continuously outperforms the competing actor environments
Erlang, Charm++, SalsaLite, Scala, ActorFoundry, and even the OpenMPI.Comment: 33 page
Requirements for implementing real-time control functional modules on a hierarchical parallel pipelined system
Analysis of a robot control system leads to a broad range of processing requirements. One fundamental requirement of a robot control system is the necessity of a microcomputer system in order to provide sufficient processing capability.The use of multiple processors in a parallel architecture is beneficial for a number of reasons, including better cost performance, modular growth, increased reliability through replication, and flexibility for testing alternate control strategies via different partitioning. A survey of the progression from low level control synchronizing primitives to higher level communication tools is presented. The system communication and control mechanisms of existing robot control systems are compared to the hierarchical control model. The impact of this design methodology on the current robot control systems is explored
Parallelizing RRT on large-scale distributed-memory architectures
This paper addresses the problem of parallelizing the Rapidly-exploring Random Tree (RRT) algorithm on large-scale distributed-memory architectures, using the Message Passing Interface. We compare three parallel versions of RRT based on classical parallelization schemes. We evaluate them on different motion planning problems and analyze the various factors influencing their performance
Learning Scheduling Algorithms for Data Processing Clusters
Efficiently scheduling data processing jobs on distributed compute clusters
requires complex algorithms. Current systems, however, use simple generalized
heuristics and ignore workload characteristics, since developing and tuning a
scheduling policy for each workload is infeasible. In this paper, we show that
modern machine learning techniques can generate highly-efficient policies
automatically. Decima uses reinforcement learning (RL) and neural networks to
learn workload-specific scheduling algorithms without any human instruction
beyond a high-level objective such as minimizing average job completion time.
Off-the-shelf RL techniques, however, cannot handle the complexity and scale of
the scheduling problem. To build Decima, we had to develop new representations
for jobs' dependency graphs, design scalable RL models, and invent RL training
methods for dealing with continuous stochastic job arrivals. Our prototype
integration with Spark on a 25-node cluster shows that Decima improves the
average job completion time over hand-tuned scheduling heuristics by at least
21%, achieving up to 2x improvement during periods of high cluster load
Two-Bit Messages are Sufficient to Implement Atomic Read/Write Registers in Crash-prone Systems
Atomic registers are certainly the most basic objects of computing science.
Their implementation on top of an n-process asynchronous message-passing system
has received a lot of attention. It has been shown that t \textless{} n/2
(where t is the maximal number of processes that may crash) is a necessary and
sufficient requirement to build an atomic register on top of a crash-prone
asynchronous message-passing system. Considering such a context, this paper
presents an algorithm which implements a single-writer multi-reader atomic
register with four message types only, and where no message needs to carry
control information in addition to its type. Hence, two bits are sufficient to
capture all the control information carried by all the implementation messages.
Moreover, the messages of two types need to carry a data value while the
messages of the two other types carry no value at all. As far as we know, this
algorithm is the first with such an optimality property on the size of control
information carried by messages. It is also particularly efficient from a time
complexity point of view
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