Listing of all papers published by Mustafa Uysal

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Applying the {CHAOS/PARTI} Library to Irregular Problems in Computational Chemistry and Computational Aerodynamics Published in Proceedings of the Scalable Parallel Libraries Conference, Mississippi State University, Starkville, MS pg: 45-46 R. Das, Y. Hwang, M. Uysal, J. Saltz, A. Sussman. This paper describes a number of optimizations that can be used to support the efficient execution of irregular problems on distributed memory parallel machines. We describe software primitives that (1) coordinate interprocessor data movement, (2) manage the storage of, and access to, copies of off-processor data, (3) minimize interprocessor communication requirements and (4) support a shared name space. The performance of the primitives is characterized by examination of kernels from real applications and from a full implementation of a large unstructured adaptive application (the molecular dynamics code CHARMM). Communication Optimizations for Irregular Scientific Computations on Distributed Memory Architechtures University of Maryland, Department of Computer Science and UMIACS Technical Reports CS-TR-3163, UMIACS-TR-93-109 Raja Das, Mustafa Uysal, Joel Saltz, Yuan-Shin Hwang. This paper describes a number of optimizations that can be used to support the efficient execution of irregular problems on distributed memory parallel machines. We describe software primitives that (1) coordinate interprocessor data movement, (2) manage the storage of, and access to, copies of off-processor data, (3) minimize interprocessor communication requirements and (4) support a shared name space. We present a detailed performance and scalability analysis of the communication primitives. This performance and scalability analysis is carried out using a workload genera tor, kernels from real applications and a large unstructured adaptive application (the molecular dynamics code CHARM M).
Published in Proceedings of the Scalable Parallel Libraries Conference, Mississippi State University, Starkville, MS pg: 45-46 R. Das, Y. Hwang, M. Uysal, J. Saltz, A. Sussman. This paper describes a number of optimizations that can be used to support the efficient execution of irregular problems on distributed memory parallel machines. We describe software primitives that (1) coordinate interprocessor data movement, (2) manage the storage of, and access to, copies of off-processor data, (3) minimize interprocessor communication requirements and (4) support a shared name space. The performance of the primitives is characterized by examination of kernels from real applications and from a full implementation of a large unstructured adaptive application (the molecular dynamics code CHARMM).
Communication Optimizations for Irregular Scientific Computations on Distributed Memory Architechtures University of Maryland, Department of Computer Science and UMIACS Technical Reports CS-TR-3163, UMIACS-TR-93-109 Raja Das, Mustafa Uysal, Joel Saltz, Yuan-Shin Hwang. This paper describes a number of optimizations that can be used to support the efficient execution of irregular problems on distributed memory parallel machines. We describe software primitives that (1) coordinate interprocessor data movement, (2) manage the storage of, and access to, copies of off-processor data, (3) minimize interprocessor communication requirements and (4) support a shared name space. We present a detailed performance and scalability analysis of the communication primitives. This performance and scalability analysis is carried out using a workload genera tor, kernels from real applications and a large unstructured adaptive application (the molecular dynamics code CHARM M).
University of Maryland, Department of Computer Science and UMIACS Technical Reports CS-TR-3163, UMIACS-TR-93-109 Raja Das, Mustafa Uysal, Joel Saltz, Yuan-Shin Hwang. This paper describes a number of optimizations that can be used to support the efficient execution of irregular problems on distributed memory parallel machines. We describe software primitives that (1) coordinate interprocessor data movement, (2) manage the storage of, and access to, copies of off-processor data, (3) minimize interprocessor communication requirements and (4) support a shared name space. We present a detailed performance and scalability analysis of the communication primitives. This performance and scalability analysis is carried out using a workload genera tor, kernels from real applications and a large unstructured adaptive application (the molecular dynamics code CHARM M).