Paper Info
Title
GRAPE - An Industrial Distributed System for Computer Vision
Abstract
GRAPE (Graph Processing Environment) is an industrial distributed computer vision system currently in use in Orbotech's Automated Optical Inspection (AOI) machines. These machines are designed for the automatic detection of defects in Flat Panel Displays (FPD), Printed Circuit Boards (PCB) and Ball Grid Arrays (BGA). The GRAPE system is designed to be easy to use for algorithm and systems engineers with little or no special training in parallel or distributed systems. Algorithms are written in standard C++ and joined together in a visual dataflow graph. The user then partitions the graph into "contexts" which are used by the system to automatically parallelize the computation. The underlying execution model of GRAPE is based on a large-grained dynamic data-flow paradigm. In contrast to traditional dataflow engines GRAPE algorithms can hold "state" over multiple executions while also making use of data parallelism. This is useful for computer vision applications, which typically need to assemble and process data collected over many execution cycles. In this paper we present an overview of the GRAPE system with its context oriented parallelism and synchronization.
Year
DOI
Venue
2005
10.1109/IPDPS.2005.235
IPDPS
Keywords
Field
DocType
systems engineer,grape algorithm,process data,computer vision system,computer vision application,grape system,multiple execution,traditional dataflow engine,computer vision,data parallelism,execution cycle,pipelines,printed circuit boards,printed circuits,data collection,parallel systems,distributed system,automatic parallelization,distributed computing,algorithm design and analysis,parallel processing,printed circuit board,electronics packaging,vision system,synchronisation,system engineering,dynamic data,ball grid array,dataflow
Computer science,Printed circuit board,Dataflow,Artificial intelligence,Automated optical inspection,Distributed computing,Computation,Computer vision,Synchronization,Parallel computing,Data parallelism,Execution model,Grid,Embedded system
Conference
ISBN
Citations 
PageRank 
0-7695-2312-9
0
0.34
References 
Authors
3
2
Name
Order
Citations
PageRank
David Minor1105.45
Shmuel Rippa215314.70