7766753
ZPL: An Array Sublanguage
The notion of isolating the “common case” is a well known computer science principle. This paper describes ZPL, a language that treats data parallelism as a common case of MIMD parallelism. This separation of concerns has many benefits. It allows us to define a clean and concise language for describing data parallel computations, and this in turn leads to efficient parallel execution. Our particular language also provides mechanisms for handling boundary conditions. We introduce the concepts, constructs and semantics of our new language, and give a simple example that contrasts ZPL with other data parallel languages.
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.
27000155
Towards a Machine-Independent Solution of Sparse Cholesky Factorization
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>>
2010014
Training a selection function for extraction
In this paper we compare performance of several heuristics in generating informative generic/query-oriented extracts for newspaper articles in order to learn how topic prominence affects the performance of each heuristic. We study how different query types can affect the performance of each heuristic and discuss the possibility of using machine learning algorithms to automatically learn good combination functions to combine several heuristics. We also briefly describe the design, implementation, and performance of a multilingual text summarization system SUMMARIST.
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.
3084140
Ranking individuals by group comparisons
This paper proposes new approaches to rank individuals from their group competition results. Many real-world problems are of this type. For example, ranking players from team games is important in some sports. We propose an exponential model to solve such problems. To estimate individual rankings through the proposed model we introduce two convex minimization formulas with easy and efficient solution procedures. Experiments on real bridge records and multi-class classification demonstrate the viability of the proposed model.
15011396
Adaptive resource management for mobile multimedia communications in asymmetric wireless network
In the multi-service wireless networks, the bandwidth asymmetry is the distinctive characteristic. To avoid wasting uplink and downlink bandwidth in asymmetric network, admissible region for the nonreal-time (NRT) calls has been proposed. But in that scheme the static guard capacity for RT and NRT calls cannot adapt to traffic variation. In addition, the differentiated QoS services to users are not considered. In this paper, we propose an adaptive guard channel reservation (AGCR) scheme, which has the following novelties: i) the guard capacity for each class is dynamically adjusted so as to adapt to dynamic traffic, ii) the blocking probabilities of classes with higher priority are kept below certain targets and iii) differentiated QoS services to users are provided by maintaining the blocking probability ratios over different classes at the predefined targets. Simulation results have demonstrated the proposed AGCR scheme can keep the blocking probabilities of classes with higher priority below certain targets, track the ratios close to the targets well while maintaining a high bandwidth utilization
5934964
Fuzzy control for guaranteeing absolute delays in Web servers
This paper presents a fuzzy control approach that guarantees absolute delays in Web servers. Previous work has proposed the use of classical PI controllers for delay guarantees. However, a disadvantage of the classical PI controller is that the system model, which is obtained by system identification, mismatches the real system and inevitably degrades the performance of the Web system. In contrast with classical PI controllers, fuzzy controllers are nonlinear and therefore independent of the accurate model of the plant, i.e. the controlled system. Hence, fuzzy controllers seem to be very suitable for Web servers. Our experiments show that fuzzy controllers indeed perform better than PI controllers presented in earlier papers