Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

The aditi deductive database system

Deductive databases generalize relational databases by providing support for recursive views and non-atomic data. Aditi is a deductive system based on the client-server model; it is inherently multi-user and capable of exploiting parallelism on shared-memory multiprocessors. The back-end uses relational technology for efficiency in the management of disk-based data and uses optimization algorithms especially developed for the bottom-up evaluation of logical queries involving recursion. The front-end interacts with the user in a logical language that has more expressive power than relational query languages. We present the structure of Aditi, discuss its components in some detail, and present performance figures.     

Granularity Analysis for Exploiting Adaptive Parallelism of Declarative Programs on Multiprocessors

1IntroductionAutomaticparallelexecutionofdeclarativelanguageprograms(e.g.functionprogramsandlogicprograms)isattractive,asitmakestheuseofparallelcomputersveryeasy,andtheprogrammerneednotbeconcernedwiththespecificsoftheunderlyingparallelarchitecture.However,ifseveralprocessorsareexecutingconcurrently,exploitingadaptiveparallelismishardduetonon-determinismoftaskgranularityanddatadependenciesamongtasks.TheearlysolutionproposedbyConeryandKibler[2]usesanorderingalgorithmtodeterminedependenciesatrun…     

激光干涉环圆心位置测定技术及应用

本文利用在平面内绕定轴旋转的线阵ＣＣＤ及微机系统自动测定激光干涉环圆心位置及应用于激光外径千分尺平行度检查仪平行度检查结果的自动数字化输出。     

EIGENVECTORS-BASED PARALLELISATION OF NESTED LOOPS WITH AFFINE DEPENDENCES

Abstract

This paper presents a method for parallelising nested loops with affine dependences. The data dependences of a program are represented exactly using a dependence matrix rather than an imprecise dependence abstraction. By a careful analysis of the eigenvectors and eigenvalues of the dependence matrix, we detect the parallelism inherent in the program, partition the iteration space of the program into sequential and parallel regions, and generate parallel code to execute these regions. For a class of programs considered in the paper, the proposed method can expose more coarse-grain and fine-grain parallelism than a hyperplane-based loop transformation.     

Some efficient solutions to the affine scheduling problem. Part II. Multidimensional time

This paper extends the algorithms which were developed in Part I to cases in which there is no affine schedule, i.e. to problems whose parallel complexity is polynomial but not linear. The natural generalization is to multidimensional schedules with lexicographic ordering as temporal succession. Multidimensional affine schedules, are, in a sense, equivalent to polynomial schedules, and are much easier to handle automatically. Furthermore, there is a strong connection between multidimensional schedules and loop nests, which allows one to prove that a static control program always has a multidimensional schedule. Roughly, a larger dimension indicates less parallelism. In the algorithm which is presented here, this dimension is computed dynamically, and is just sufficient for scheduling the source program. The algorithm lends itself to a divide and conquer strategy. The paper gives some experimental evidence for the applicability, performances and limitations of the algorithm.     

Accelerating sequential programs on commodity multi-core processors

A recently proposed pipelined multithreading (PMT) technique exhibits wide applicability in parallelizing general sequential programs on multi-core processors. However, significant inter-core communication overhead limits PMT performance and prevents its commercial utilization. A simple and effective clustered pipelined multithreading (CPMT) approach is presented to accelerate sequential programs on commodity multi-core processors. This CPMT technique adopts a clustered communication mechanism that can yield very low average communication overhead by eliminating false sharing as well as reducing communication operation and transit delays in the software-only approach. A single-producer/single-consumer concurrent lock-free clusteredQueue algorithm based on a two-level queue structure is also proposed. The accuracy of CPMT is theoretically demonstrated. The performances of the algorithm and CPMT are evaluated on a commodity AMD Phenom four-core processor. The number of enqueue and dequeue times of the algorithm are 20.8 and 23 cycles given an appropriate parameter, respectively. The speedup of CPMT ranges from 13.1% to 119.8% for typical loops extracted from the SPEC CPU 2000 benchmark suite.     

Kokkos: Enabling manycore performance portability through polymorphic memory access patterns

The manycore revolution can be characterized by increasing thread counts, decreasing memory per thread, and diversity of continually evolving manycore architectures. High performance computing (HPC) applications and libraries must exploit increasingly finer levels of parallelism within their codes to sustain scalability on these devices. A major obstacle to performance portability is the diverse and conflicting set of constraints on memory access patterns across devices. Contemporary portable programming models address manycore parallelism (e.g., OpenMP, OpenACC, OpenCL) but fail to address memory access patterns. The Kokkos C++ library enables applications and domain libraries to achieve performance portability on diverse manycore architectures by unifying abstractions for both fine-grain data parallelism and memory access patterns. In this paper we describe Kokkos’ abstractions, summarize its application programmer interface (API), present performance results for unit-test kernels and mini-applications, and outline an incremental strategy for migrating legacy C++ codes to Kokkos. The Kokkos library is under active research and development to incorporate capabilities from new generations of manycore architectures, and to address a growing list of applications and domain libraries.