Shared memory models have been criticized for years for failing to model essential realities of parallel machines. Given the current wave of popular message-passing and distributed memory models (e.g., BSP, LOGP), it is natural to ask whether shared memory models have outlived any usefulness they may have had. In this invited position papel; we discuss the continuing importance of shared memory models in the design and analysis of par-allel algorithms. We describe a new model, the Queuing Shared Memory (QSM) model, that accounts for limited communication bandwidth while still providing a shared memory abstraction, and provide evidence of its practicality. Finally, we discuss important areas for future models research. We argue that the comp...
Abstract We present work-preserving emulations with small slowdown between LogP and two other parall...
In this paper we identify the factors that affect the derivation of computation and data partitions ...
For the design and analysis of algorithms that process huge data sets, a machine model is needed tha...
There has been a great deal of interest recently in the development of general-purpose bridging mode...
Parallel programming models should attempt to satisfy two conflicting goals. On one hand, they shoul...
Parallel programming models should attempt to satisfy two conflicting goals. On one hand, they shoul...
190 pages ISSN 1238-6944, ISBN 951-708-693-8 Keywords: parallel computing, shared memory, modeling...
The goal of this work was to examine existing shared memory parallel programming models, figure out ...
Data locality is a well-recognized requirement for the development of any parallel application, but ...
In this work, a model of computation for shared memory parallelism is presented. To address fundamen...
In this paper we present a new approach to benchmark the performance of shared memory systems. This ...
Most current multiprocessor architectures and shared memory parallel program-ming languages are not ...
In this paper we present a new approach to benchmark the performance of shared memory systems. This ...
The traditional consistency requirements of shared memory are expensive to provide both in large sc...
For the design and analysis of algorithms that process huge data sets, a machine model is needed tha...
Abstract We present work-preserving emulations with small slowdown between LogP and two other parall...
In this paper we identify the factors that affect the derivation of computation and data partitions ...
For the design and analysis of algorithms that process huge data sets, a machine model is needed tha...
There has been a great deal of interest recently in the development of general-purpose bridging mode...
Parallel programming models should attempt to satisfy two conflicting goals. On one hand, they shoul...
Parallel programming models should attempt to satisfy two conflicting goals. On one hand, they shoul...
190 pages ISSN 1238-6944, ISBN 951-708-693-8 Keywords: parallel computing, shared memory, modeling...
The goal of this work was to examine existing shared memory parallel programming models, figure out ...
Data locality is a well-recognized requirement for the development of any parallel application, but ...
In this work, a model of computation for shared memory parallelism is presented. To address fundamen...
In this paper we present a new approach to benchmark the performance of shared memory systems. This ...
Most current multiprocessor architectures and shared memory parallel program-ming languages are not ...
In this paper we present a new approach to benchmark the performance of shared memory systems. This ...
The traditional consistency requirements of shared memory are expensive to provide both in large sc...
For the design and analysis of algorithms that process huge data sets, a machine model is needed tha...
Abstract We present work-preserving emulations with small slowdown between LogP and two other parall...
In this paper we identify the factors that affect the derivation of computation and data partitions ...
For the design and analysis of algorithms that process huge data sets, a machine model is needed tha...