scholarly journals Performance Issues in High Performance Fortran Implementations of Sensor-Based Applications

1997 ◽  
Vol 6 (1) ◽  
pp. 59-72 ◽  
Author(s):  
David R. O'hallaron ◽  
Jon Webb ◽  
Jaspal Subhlok
Keyword(s):  
High Performance ◽  
Parallel Machines ◽  
Radar Imaging ◽  
Synthetic Aperture ◽  
Application Domain ◽  
Resonance Imaging ◽  
High Performance Fortran ◽  
Intel Paragon ◽  
Independent Loops ◽  
Tracking Radar

Applications that get their inputs from sensors are an important and often overlooked application domain for High Performance Fortran (HPF). Such sensor-based applications typically perform regular operations on dense arrays, and often have latency and through put requirements that can only be achieved with parallel machines. This article describes a study of sensor-based applications, including the fast Fourier transform, synthetic aperture radar imaging, narrowband tracking radar processing, multibaseline stereo imaging, and medical magnetic resonance imaging. The applications are written in a dialect of HPF developed at Carnegie Mellon, and are compiled by the Fx compiler for the Intel Paragon. The main results of the study are that (1) it is possible to realize good performance for realistic sensor-based applications written in HPF and (2) the performance of the applications is determined by the performance of three core operations: independent loops (i.e., loops with no dependences between iterations), reductions, and index permutations. The article discusses the implications for HPF implementations and introduces some simple tests that implementers and users can use to measure the efficiency of the loops, reductions, and index permutations generated by an HPF compiler.

scholarly journals Scientific Programming with High Performance Fortran: A Case Study Using the xHPF Compiler

1997 ◽  
Vol 6 (1) ◽  
pp. 127-152
Author(s):  
Eric De Sturler ◽  
Volker Strumpen
Keyword(s):  
High Performance ◽  
Parallel Implementation ◽  
Gaussian Elimination ◽  
Primary Objective ◽  
Matrix Product ◽  
Dense Matrix ◽  
High Performance Fortran ◽  
Partial Pivoting ◽  
Intel Paragon

Recently, the first commercial High Performance Fortran (HPF) subset compilers have appeared. This article reports on our experiences with the xHPF compiler of Applied Parallel Research, version 1.2, for the Intel Paragon. At this stage, we do not expect very High Performance from our HPF programs, even though performance will eventually be of paramount importance for the acceptance of HPF. Instead, our primary objective is to study how to convert large Fortran 77 (F77) programs to HPF such that the compiler generates reasonably efficient parallel code. We report on a case study that identifies several problems when parallelizing code with HPF; most of these problems affect current HPF compiler technology in general, although some are specific for the xHPF compiler. We discuss our solutions from the perspective of the scientific programmer, and presenttiming results on the Intel Paragon. The case study comprises three programs of different complexity with respect to parallelization. We use the dense matrix-matrix product to show that the distribution of arrays and the order of nested loops significantly influence the performance of the parallel program. We use Gaussian elimination with partial pivoting to study the parallelization strategy of the compiler. There are various ways to structure this algorithm for a particular data distribution. This example shows how much effort may be demanded from the programmer to support the compiler in generating an efficient parallel implementation. Finally, we use a small application to show that the more complicated structure of a larger program may introduce problems for the parallelization, even though all subroutines of the application are easy to parallelize by themselves. The application consists of a finite volume discretization on a structured grid and a nested iterative solver. Our case study shows that it is possible to obtain reasonably efficient parallel programs with xHPF, although the compiler needs substantial support from the programmer.

scholarly journals PGHPF – An Optimizing High Performance Fortran Compiler for Distributed Memory Machines

1997 ◽  
Vol 6 (1) ◽  
pp. 29-40 ◽  
Author(s):  
Zeki Bozkus ◽  
Larry Meadows ◽  
Steven Nakamoto ◽  
Vincent Schuster ◽  
Mark Young
Keyword(s):  
High Performance ◽  
Distributed Memory ◽  
Parallel Machines ◽  
High Efficiency ◽  
Memory Systems ◽  
Production Quality ◽  
Distributed Memory Machines ◽  
High Performance Fortran ◽  
Application Developers ◽  
Efficient Software

High Performance Fortran (HPF) is the first widely supported, efficient, and portable parallel programming language for shared and distributed memory systems. HPF is realized through a set of directive-based extensions to Fortran 90. It enables application developers and Fortran end-users to write compact, portable, and efficient software that will compile and execute on workstations, shared memory servers, clusters, traditional supercomputers, or massively parallel processors. This article describes a production-quality HPF compiler for a set of parallel machines. Compilation techniques such as data and computation distribution, communication generation, run-time support, and optimization issues are elaborated as the basis for an HPF compiler implementation on distributed memory machines. The performance of this compiler on benchmark programs demonstrates that high efficiency can be achieved executing HPF code on parallel architectures.

scholarly journals An Algebraic Machinery for Optimizing Data Motion for HPF

1997 ◽  
Vol 6 (3) ◽  
pp. 297-325
Author(s):  
Jan-Jan Wu ◽  
Marina C. Chen
Keyword(s):  
High Performance ◽  
Parallel Machines ◽  
Compiler Optimization ◽  
Optimization Technique ◽  
Massively Parallel ◽  
High Performance Fortran ◽  
Fortran 90

This paper describes a general compiler optimization technique that reduces communica tion over-head for FORTRAN-90 (and High Performance FORTRAN) implementations on massively parallel machines.

scholarly journals High Performance Fortran: A Practical Analysis

1994 ◽  
Vol 3 (3) ◽  
pp. 187-199 ◽  
Author(s):  
Allan Knies ◽  
Matthew O'keefe ◽  
Tom Macdonald
Keyword(s):  
High Performance ◽  
Parallel Machines ◽  
Production Quality ◽  
Efficient Production ◽  
Data Parallel ◽  
High Performance Fortran ◽  
Multiple Data ◽  
Computing Industry ◽  
Application Developers ◽  
Important Design

The recently released high performance Fortran forum (HPFF) proposal has stirred much interest in the high performance computing industry. HPFF's most important design goal is to create a language that has source code portability and that achieves high performance on single instruction multiple data (SIMD), distributed-memory multiple instruction multiple data (MIMD), and shared-memory MIMD architectures. The HPFF proposal brings to the forefront many questions about design of portable and efficient languages for parallel machines. In this article, we discuss issues that need to be addressed before an efficient production quality compiler will be available for any such language. We examine some specific issues that are related to HPF's model of computation and analyze several implementation issues. We also provide some results from another data parallel compiler to help gain insight on some of the implementation issues that are relevant to HPF. Finally, we provide a summary of options currently available for application developers in industry.

Design strategy of ultrasmall Gd2O3 nanoparticles for T1 MRI with high performance

2021 ◽  
Author(s):  
Jianfeng Yang ◽  
Pengyuan Shan ◽  
Qingling Zhao ◽  
Shuquan Zhang ◽  
Lanlan Li ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
High Performance ◽  
Design Strategy ◽  
Resonance Imaging ◽  
Relative Time ◽  
Time Parameters ◽  
Gd2o3 Nanoparticles

It is still a big challenge for designing Gd3+ based nanoparticles (NPs) for T1 MRI (Magnetic Resonance Imaging) with high performance and clarifying the effects of relative time parameters for...

Sign in / Sign up

Export Citation Format

Share Document