Automatic Object Colocation Based on Read Barriers

نویسندگان

  • Christian Wimmer
  • Hanspeter Mössenböck
چکیده

Object colocation is an optimization that reduces memory access costs by grouping together heap objects so that their order in memory matches their access order in the program. We implemented this optimization for Sun Microsystems’ Java HotSpot VM. The garbage collector, which moves objects during collection, assigns consecutive addresses to connected objects and handles them as atomic units. We use read barriers inserted by the just-in-time compiler to detect the most frequently accessed fields per class. These “hot fields” are added to so-called hot-field tables, which are then used by the garbage collector for colocation decisions. Read barriers that are no longer needed are removed in order to reduce the overhead. Our analysis is performed automatically at run time and requires no actions on the side of the programmer. We measured the impact of object colocation on the young and the old generation of the garbage collector, as well as the difference between dynamic colocation using read barriers and a static colocation strategy where colocation decisions are done at compile time. Our measurements show that object colocation works best for the young generation using a read-barrier-based approach.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...

متن کامل

Automatic Road Detection and Extraction From MultiSpectral Images Using a New Hierarchical Object-based Method

Road detection and Extraction is one of the most important issues in photogrammetry, remote sensing and machine vision. A great deal of research has been done in this area based on multispectral images, which are mostly relatively good results. In this paper, a novel automated and hierarchical object-based method for detecting and extracting of roads is proposed. This research is based on the M...

متن کامل

Automatic Interpretation of UltraCam Imagery by Combination of Support Vector Machine and Knowledge-based Systems

With the development of digital sensors, an increasing number of high-resolution images are available. Interpretation of these images is not possible manually, which necessitates seeking for practical, fast and automatic solutions to solve the environmental and location-based management problems. The land cover classification using high-resolution imagery is a difficult process because of the c...

متن کامل

Object-Based Classification of UltraCamD Imagery for Identification of Tree Species in the Mixed Planted Forest

This study is a contribution to assess the high resolution digital aerial imagery for semi-automatic analysis of tree species identification. To maximize the benefit of such data, the object-based classification was conducted in a mixed forest plantation. Two subsets of an UltraCam D image were geometrically corrected using aero-triangulation method. Some appropriate transformations were perfor...

متن کامل

Kohonen Self Organizing for Automatic Identification of Cartographic Objects

Automatic identification and localization of cartographic objects in aerial and satellite images have gained increasing attention in recent years in digital photogrammetry and remote sensing. Although the automatic extraction of man made objects in essence is still an unresolved issue, the man made objects can be extracted from aerial photos and satellite images. Recently, the high-resolution s...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006