32008979
Isomorphic Path Decompositions of Crowns
40521773
Cycle decompositions of crowns
Abstract For an integer n ⩾3, the crown S n 0 is defined to be the graph with vertex set { x 0 , x 1 ,…, x n −1 , y 0 , y 1 ,…, y n −1 } and edge set {x i y j : 0⩽i,j⩽n−1, i≠j} . In this paper we give some sufficient conditions for the edge decomposition of the crown into isomorphic cycles.
12579085
The super laceability of the hypercubes
A k-container C(u,v) of a graph G is a set of k disjoint paths joining u to v. A k-container C(u, v) is a k*-container if every vertex of G is incident with a path in C(u,v). A bipartite graph G is k*-laceable if there exists a k*-container between any two vertices u, v from different partite set of G. A bipartite graph G with connectivity k is super laceable if it is i*-laceable for all i ≤ k. A bipartite graph G with connectivity k is f-edge fault-tolerant super laceable if G - F is i*-laceable for any 1 ≤ i ≤ k-f and for any edge subset F with |F|=f r is super laceable. Moreover, Q r is f-edge fault-tolerant super laceable for any f ≤ r - 2.
26305379
A parallel decoding algorithm for IFS codes without transient behavior
Iterated function systems (IFSs) have received great attention in encoding and decoding fractal images. Barnsley (1988) has shown that IFSs for image compression can achieve a very high compression ratio for a single image. However, the major drawback of such a technique is the large computation load required to both encode and decode a fractal image. We provide a novel algorithm to decode IFS codes. The main features of this algorithm are that it is very suitable for parallel implementation and has no transient behavior. Also, from the decoding process of this method we can understand the encoding procedure explicitly. One example is illustrated to demonstrate the quality of its performance.
15307682
Accommodating polymorphic data decompositions in explicitly parallel programs
Explicitly parallel programs have the potential for greater performance than their implicitly parallel counterparts. However, this benefit can be accompanied by additional programming difficulties. We address one particular problem that has implications for both scalability and portability: the need for programs do accommodate diverse data decompositions. We explain why programs with explicit communication have difficulties in handling changes in data decomposition, and we present a solution to this problem which involves the notions of derivative functions and configuration parameters. We illustrate the technique by using three different data decompositions to solve the Modified Gram-Schmidt method on four parallel machines.<<ETX>>
1280007
Memory Prefetching Using Adaptive Stream Detection
We present adaptive stream detection, a simple technique for modulating the aggressiveness of a stream prefetcher to match a workload's observed spatial locality. We use this concept to design a prefetcher that resides on an on-chip memory controller. The result is a prefetcher with small hardware costs that can exploit workloads with low amounts of spatial locality. Using highly accurate simulators for the IBM Power5+, we show that this prefetcher improves performance of the SPEC2006fp benchmarks by an average of 32.7% when compared against a Power5+ that performs no prefetching. On a set of 5 commercial benchmarks that have low spatial locality, this prefetcher improves performance by an average of 15.1%. When compared against a typical Power5+ that does perform processor-side prefetching, the average performance improvement of these benchmark suites is 10.2% and 8.4%. We also evaluate the power and energy impact of our technique. For the same benchmark suites, DRAM power consumption increases by less than 3%, while energy usage decreases by 9.8% and 8.2%, respectively. Moreover, the power consumption of the prefetcher itself is low; it is estimated to increase the power consumption of the Power5+ chip by 0.06%
7601651
Hierarchical Cache Consistency in a WAN
This paper explores ways to provide improved consistency for Internet applications that scale to millions of clients. We make four contributions. First, we identify how workloads affect the scalability of cache consistency algorithms. Second, we define two primitive mechanisms, split and join, for growing and shrinking consistency hierarchies, and we present a simple mechanism for implementing them. Third, we describe and evaluate policies for using split and join to address the fault tolerance and performance challenges of consistency hierarchies. Fourth, using synthetic workload and trace-based simulation, we compare various algorithms for maintaining strong consistency in a range of hierarchy configurations. Our results indicate that a promising configuration for providing strong consistency in a WAN is a two-level consistency hierarchy where servers and proxies work to maintain consistency for data cached at clients. Specifically, by adapting to clients' access patterns, two-level hierarchies reduce the read latency for demanding workloads without introducing excessive overhead for nondemanding workloads. Also, they can improve scalability by orders of magnitude. Furthermore, this configuration is easy to deploy by augmenting proxies, and it allows invalidation messages to traverse firewalls.