1407089
Volume Leases for Consistency in Large-Scale Systems
This article introduces volume leases as a mechanism for providing server-driven cache consistency for large-scale, geographically distributed networks. Volume leases retain the good performance, fault tolerance, and server scalability of the semantically weaker client-driven protocols that are now used on the Web. Volume leases are a variation of object leases, which were originally designed for distributed file systems. However, whereas traditional object leases amortize overheads over long lease periods, volume leases exploit spatial locality to amortize overheads across multiple objects in a volume. This approach allows systems to maintain good write performance even in the presence of failures. Using trace-driven simulation, we compare three volume lease algorithms against four existing cache consistency algorithms and show that our new algorithms provide strong consistency while maintaining scalability and fault-tolerance. For a trace-based workload of Web accesses, we find that volumes can reduce message traffic at servers by 40 percent compared to a standard lease algorithm, and that volumes can considerably reduce the peak load at servers when popular objects are modified.
7870525
Adaptive History-Based Memory Schedulers
As memory performance becomes increasingly important to overall system performance, the need to carefully schedule memory operations also increases. This paper presents a new approach to memory scheduling that considers the history of recently scheduled operations. This history-based approach provides two conceptual advantages: (1) it allows the scheduler to better reason about the delays associated with its scheduling decisions, and (2) it allows the scheduler to select operations so that they match the program's mixture of Reads and Writes, thereby avoiding certain bottlenecks within the memory controller. We evaluate our solution using a cycle-accurate simulator for the recently announced IBM Power5. When compared with an in-order scheduler, our solution achieves IPC improvements of 10.9% on the NAS benchmarks and 63% on the data-intensive Stream benchmarks. Using microbenchmarks, we illustrate the growing importance of memory scheduling in the context of CMP's, hardware controlled prefetching, and faster CPU speeds.
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>>
27000155
Towards a Machine-Independent Solution of Sparse Cholesky Factorization
5795237
The portable parallel implementation of two novel mathematical biology algorithms in ZPL
This paper shows that mathematical models of biological pattern formation are ideally suited to data parallelism. We present two new algorithms, one for simulating the dynamic structure of fibroblasts, and the other for studying the self-organization of motile bacteria. We describe implementations of these algorithms using a high level data parallel language called ZPL, and we give performance results for the Kendall Square Research KSR-2 and the Intel Paragon that include comparisons against sequential Fortran.
9009444
A Portable Parallel N-Body Solver
We present parallel solutions for direct and fast n-body solvers written in the ZPL language. We describe the direct solver, compare its performance against a sequential C program, and show performance results for two very different parallel machines; the KSR-2 and the Paragon. We also discuss the implementation of the fast solver in ZPL, including factors pertinent to data movement.
16749457
Approximate Performance Analysis of Web Services Flow Using Stochastic Petri Net
Web services provide a language-neutral, loosely-coupled, and platform-independent way for linking applications within organizations or enterprises across the Internet. In such a scenario, quantitative characteristics such as service execution throughput should be evaluated to measure the system performance. Usually, the first step is to define an abstract workflow model, for example Stochastic Petri Net Models. However, large system always raises the problem of state explosion. In this paper, we discuss a set of simplification rules for five basic structures of web service flow: sequential, parallel, conditional, loop and mutex. Our approach can effectively reduce the state space and is applied to the performance analysis of a web service flow management system.
41121683
Decomposition Methods for Linear Support Vector Machines
In this letter, we show that decomposition methods with alpha seeding are extremely useful for solving a sequence of linear support vector machines (SVMs) with more data than attributes. This strategy is motivated by Keerthi and Lin (2003), who proved that for an SVM with data not linearly separable, after C is large enough, the dual solutions have the same free and bounded components. We explain why a direct use of decomposition methods for linear SVMs is sometimes very slow and then analyze why alpha seeding is much more effective for linear than nonlinear SVMs. We also conduct comparisons with other methods that are efficient for linear SVMs and demonstrate the effectiveness of alpha seeding techniques in model selection.
52872372
Modeling and Performance Analysis of a Multiserver Multiqueue System on the Grid
Grid computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and high-performance orientation. A Grid integrates and coordinates resources and users that live within different control domains with the goal of delivering nontrivial quality of service (QoS). Consequently, task management and scheduling is of central importance for the Grid-based systems. In this paper, we model the task dispatching and selecting on the distributed Grid computing system by a multiserver multiqueue (MSMQ) model, and propose a modeling and analysis technique based on Stochastic Petri Net (SPN) methods. An approximate analysis technique is also proposed to reduce the complexity of the model.
17351609
Two-dimensional LMS adaptive linear phase filters
Two-dimensional least mean square (2D LMS) adaptive filters are used in image processing applications for reducing noise. A new two-dimensional LMS algorithm is proposed, in which an additional linear phase constraint is added to the constraints of the existing 2D LMS algorithms. Compared with the conventional algorithms, the results show that the proposed algorithm is much more efficient both in computation time and memory storage.<<ETX>>
7645082
An annotation language for optimizing software libraries
This paper introduces an annotation language and a compiler that together can customize a library implementation for specific application needs. Our approach is distinguished by its ability to exploit high level, domain-specific information in the customization process. In particular, the annotations provide semantic information that enables our compiler to analyze and optimize library operations as if they were primitives of a domain-specific language. Thus, our approach yields many of the performance benefits of domain-specific languages, without the effort of developing a new compiler for each domain.
This paper presents the annotation language, describes its role in optimization, and illustrates the benefits of the overall approach. Using a partially implemented compiler, we show how our system can significantly improve the performance of two applications written using the PLAPACK parallel linear algebra library.