18,135 research outputs found
Enhancing the performance of Decoupled Software Pipeline through Backward Slicing
The rapidly increasing number of cores available in multicore processors does
not necessarily lead directly to a commensurate increase in performance:
programs written in conventional languages, such as C, need careful
restructuring, preferably automatically, before the benefits can be observed in
improved run-times. Even then, much depends upon the intrinsic capacity of the
original program for concurrent execution. The subject of this paper is the
performance gains from the combined effect of the complementary techniques of
the Decoupled Software Pipeline (DSWP) and (backward) slicing. DSWP extracts
threadlevel parallelism from the body of a loop by breaking it into stages
which are then executed pipeline style: in effect cutting across the control
chain. Slicing, on the other hand, cuts the program along the control chain,
teasing out finer threads that depend on different variables (or locations).
parts that depend on different variables. The main contribution of this paper
is to demonstrate that the application of DSWP, followed by slicing offers
notable improvements over DSWP alone, especially when there is a loop-carried
dependence that prevents the application of the simpler DOALL optimization.
Experimental results show an improvement of a factor of ?1.6 for DSWP + slicing
over DSWP alone and a factor of ?2.4 for DSWP + slicing over the original
sequential code
Recommended from our members
Using topological sweep to extract the boundaries of regions in maps represented by region quadtrees
A variant of the plane sweep paradigm known as topological sweep is adapted to solve geometric problems involving two-dimensional regions when the underlying representation is a region quadtree. The utility of this technique is illustrated by showing how it can be used to extract the boundaries of a map in O(M) space and O(Ma(M)) time, where M is the number of quad tree blocks in the map, and a(·) is the (extremely slowly growing) inverse of Ackerman's function. The algorithm works for maps that contain multiple regions as well as holes. The algorithm makes use of active objects (in the form of regions) and an active border. It keeps track of the current position in the active border so that at each step no search is necessary. The algorithm represents a considerable improvement over a previous approach whose worst-case execution time is proportional to the product of the number of blocks in the map and the resolution of the quad tree (i.e., the maximum level of decomposition). The algorithm works for many different quadtree representations including those where the quadtree is stored in external storage
Hierarchical Up/Down Routing Architecture for Ethernet backbones and campus networks
We describe a new layer two distributed and scalable routing architecture. It uses an automatic hierarchical node identifier assignment mechanism associated to the rapid spanning tree protocol. Enhanced up/down mechanisms are used to prohibit some turns at nodes to break cycles, instead of blocking links like the spannning tree protocol does. The protocol performance is similar or better than other turn prohibition algorithms recently proposed with lower complexity O(Nd) and better scalability. Simulations show that the fraction of prohibited turns over random networks is less than 0.2. The effect of root bridge election on the performance of the protocol is limited both in the random and regular networks studied. The use of hierarchical, tree-descriptive addresses simplifies the routing, and avoids the need of all nodes having a global knowleddge of the network topology. Routing frames through the hierarchical tree at very high speed is possible by progressive decoding of frame destination address, without routing tables or port address learning. Coexistence with standard bridges is achieved using combined devices: bridges that forward the frames having global destination MAC addresses as standard bridges and frames with local MAC frames with the proposed protocol.Publicad
Community structures and role detection in music networks
We analyze the existence of community structures in two different social
networks obtained from similarity and collaborative features between musical
artists. Our analysis reveals some characteristic organizational patterns and
provides information about the driving forces behind the growth of the
networks. In the similarity network, we find a strong correlation between
clusters of artists and musical genres. On the other hand, the collaboration
network shows two different kinds of communities: rather small structures
related to music bands and geographic zones, and much bigger communities built
upon collaborative clusters with a high number of participants related through
the period the artists were active. Finally, we detect the leading artists
inside their corresponding communities and analyze their roles in the network
by looking at a few topological properties of the nodes.Comment: 14 pages 7 figure
Structure of Heterogeneous Networks
Heterogeneous networks play a key role in the evolution of communities and
the decisions individuals make. These networks link different types of
entities, for example, people and the events they attend. Network analysis
algorithms usually project such networks unto simple graphs composed of
entities of a single type. In the process, they conflate relations between
entities of different types and loose important structural information. We
develop a mathematical framework that can be used to compactly represent and
analyze heterogeneous networks that combine multiple entity and link types. We
generalize Bonacich centrality, which measures connectivity between nodes by
the number of paths between them, to heterogeneous networks and use this
measure to study network structure. Specifically, we extend the popular
modularity-maximization method for community detection to use this centrality
metric. We also rank nodes based on their connectivity to other nodes. One
advantage of this centrality metric is that it has a tunable parameter we can
use to set the length scale of interactions. By studying how rankings change
with this parameter allows us to identify important nodes in the network. We
apply the proposed method to analyze the structure of several heterogeneous
networks. We show that exploiting additional sources of evidence corresponding
to links between, as well as among, different entity types yields new insights
into network structure
- …