Multi-model parallel programming in psyche
PPOPP '90 Proceedings of the second ACM SIGPLAN symposium on Principles & practice of parallel programming
ParC—an extension of C for shared memory parallel processing
Software—Practice & Experience
Lazy release consistency for distributed shared memory
Lazy release consistency for distributed shared memory
Executing multithreaded programs efficiently
Executing multithreaded programs efficiently
POPL '98 Proceedings of the 25th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Computation-centric memory models
Proceedings of the tenth annual ACM symposium on Parallel algorithms and architectures
The implementation of the Cilk-5 multithreaded language
PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
High Performance Cluster Computing: Programming and Applications
High Performance Cluster Computing: Programming and Applications
A Multi-Paradigm Object Oriented Parallel Environment
Proceedings of the 8th International Symposium on Parallel Processing
Supporting multiple parallel programming paradigms on top of the Millipede virtual parallel machine
HIPS '97 Proceedings of the 1997 Workshop on High-Level Programming Models and Supportive Environments (HIPS '97)
Parallel programming in multi-paradigm clusters
HPDC '97 Proceedings of the 6th IEEE International Symposium on High Performance Distributed Computing
Cilk: Efficient Multithreaded Computing
Cilk: Efficient Multithreaded Computing
Portable high-performance programs
Portable high-performance programs
A Transparent Distributed Shared Memory for Clustered Symmetric Multiprocessors
The Journal of Supercomputing
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A parallel programming paradigm indicates the way to express applications. It also restricts the algorithms that may be used in the applications. Unfortunately, runtime systems for parallel computing often impose a particular programming paradigm. For a wider choice of algorithms, it is therefore desirable to support more than one paradigm.In this paper, we propose a formalism for modeling parallel programming paradigms from a graph-theoretic view of their execution instance dag and the memory consistency assumptions. This model allows us to formally reason about the properties of parallel programming paradigms that are hitherto only known informally and intuitively. We propose the concept of general paradigm and show that the single program multiple data, the divide and conquer, and the master/slave paradigms are all sub-sets of this general paradigm. We will also propose, a super set of these three paradigms which we called the mixed paradigm and introduce the RC_dag memory consistency model.We also present our work on SilkRoad II, a variant of the Cilk runtime system for cluster computing. What is unique about SilkRoad II is its memory model which supports multiple paradigms with the underlying software distributed shared memory. Our experimental results show that the stronger RC_dag can achieve performance comparable to LC of Cilk while supporting a bigger set of paradigms with rather good performance.