28,147 research outputs found
Gunrock: GPU Graph Analytics
For large-scale graph analytics on the GPU, the irregularity of data access
and control flow, and the complexity of programming GPUs, have presented two
significant challenges to developing a programmable high-performance graph
library. "Gunrock", our graph-processing system designed specifically for the
GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on
operations on a vertex or edge frontier. Gunrock achieves a balance between
performance and expressiveness by coupling high performance GPU computing
primitives and optimization strategies with a high-level programming model that
allows programmers to quickly develop new graph primitives with small code size
and minimal GPU programming knowledge. We characterize the performance of
various optimization strategies and evaluate Gunrock's overall performance on
different GPU architectures on a wide range of graph primitives that span from
traversal-based algorithms and ranking algorithms, to triangle counting and
bipartite-graph-based algorithms. The results show that on a single GPU,
Gunrock has on average at least an order of magnitude speedup over Boost and
PowerGraph, comparable performance to the fastest GPU hardwired primitives and
CPU shared-memory graph libraries such as Ligra and Galois, and better
performance than any other GPU high-level graph library.Comment: 52 pages, invited paper to ACM Transactions on Parallel Computing
(TOPC), an extended version of PPoPP'16 paper "Gunrock: A High-Performance
Graph Processing Library on the GPU
A Configurable Transport Layer for CAF
The message-driven nature of actors lays a foundation for developing scalable
and distributed software. While the actor itself has been thoroughly modeled,
the message passing layer lacks a common definition. Properties and guarantees
of message exchange often shift with implementations and contexts. This adds
complexity to the development process, limits portability, and removes
transparency from distributed actor systems.
In this work, we examine actor communication, focusing on the implementation
and runtime costs of reliable and ordered delivery. Both guarantees are often
based on TCP for remote messaging, which mixes network transport with the
semantics of messaging. However, the choice of transport may follow different
constraints and is often governed by deployment. As a first step towards
re-architecting actor-to-actor communication, we decouple the messaging
guarantees from the transport protocol. We validate our approach by redesigning
the network stack of the C++ Actor Framework (CAF) so that it allows to combine
an arbitrary transport protocol with additional functions for remote messaging.
An evaluation quantifies the cost of composability and the impact of individual
layers on the entire stack
Gunrock: A High-Performance Graph Processing Library on the GPU
For large-scale graph analytics on the GPU, the irregularity of data access
and control flow, and the complexity of programming GPUs have been two
significant challenges for developing a programmable high-performance graph
library. "Gunrock", our graph-processing system designed specifically for the
GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on
operations on a vertex or edge frontier. Gunrock achieves a balance between
performance and expressiveness by coupling high performance GPU computing
primitives and optimization strategies with a high-level programming model that
allows programmers to quickly develop new graph primitives with small code size
and minimal GPU programming knowledge. We evaluate Gunrock on five key graph
primitives and show that Gunrock has on average at least an order of magnitude
speedup over Boost and PowerGraph, comparable performance to the fastest GPU
hardwired primitives, and better performance than any other GPU high-level
graph library.Comment: 14 pages, accepted by PPoPP'16 (removed the text repetition in the
previous version v5
The Design of a System Architecture for Mobile Multimedia Computers
This chapter discusses the system architecture of a portable computer, called Mobile Digital Companion, which provides support for handling multimedia applications energy efficiently. Because battery life is limited and battery weight is an important factor for the size and the weight of the Mobile Digital Companion, energy management plays a crucial role in the architecture. As the Companion must remain usable in a variety of environments, it has to be flexible and adaptable to various operating conditions. The Mobile Digital Companion has an unconventional architecture that saves energy by using system decomposition at different levels of the architecture and exploits locality of reference with dedicated, optimised modules. The approach is based on dedicated functionality and the extensive use of energy reduction techniques at all levels of system design. The system has an architecture with a general-purpose processor accompanied by a set of heterogeneous autonomous programmable modules, each providing an energy efficient implementation of dedicated tasks. A reconfigurable internal communication network switch exploits locality of reference and eliminates wasteful data copies
Improving the scalability of parallel N-body applications with an event driven constraint based execution model
The scalability and efficiency of graph applications are significantly
constrained by conventional systems and their supporting programming models.
Technology trends like multicore, manycore, and heterogeneous system
architectures are introducing further challenges and possibilities for emerging
application domains such as graph applications. This paper explores the space
of effective parallel execution of ephemeral graphs that are dynamically
generated using the Barnes-Hut algorithm to exemplify dynamic workloads. The
workloads are expressed using the semantics of an Exascale computing execution
model called ParalleX. For comparison, results using conventional execution
model semantics are also presented. We find improved load balancing during
runtime and automatic parallelism discovery improving efficiency using the
advanced semantics for Exascale computing.Comment: 11 figure
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Investigating distributed simulation with COTS simulation packages: Experiences with Simul8 and the HLA
Commercial-off-the-shelf simulation packages (CSPs) are used widely in industry. Several research groups are currently working towards the creation of distributed simulation with these CSPs. The motivations to do this are various and are largely unproven as there are very few good examples of this kind of distributed simulation in practice. Our goal is therefore to create a distributed simulation environment using CSPs that will allow end users to make their own decisions as to whether this technology will be useful. This paper presents continuing research in creating such an environment using the CSP Simul8 and the High Level Architecture, the IEEE 1516 standard for distributed simulation. The scope of this paper is limited to the CSPI-PDG Type I Interoperability Reference Model
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