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Barton P Miller – One of the best experts on this subject based on the ideXlab platform.

  • anywhere any time binary Instrumentation
    Workshop on Program Analysis For Software Tools and Engineering, 2011
    Co-Authors: Andrew R Bernat, Barton P Miller
    Abstract:

    The Dyninst binary Instrumentation and analysis framework distinguishes itself from other binary Instrumentation tools through its abstract, machine independent interface; its emphasis on anywhere, any-time binary Instrumentation; and its low overhead that is proportional to the number of instrumented locations. Dyninst represents the program in terms of familiar control flow structures such as functions, loops, and basic blocks, and users manipulate these representations to insert Instrumentation anywhere in the binary. We use graph transformation techniques to insure that this Instrumentation executes when desired even when instrumenting highly optimized (or malicious) code that other instrumenters cannot correctly instrument. Unlike other binary instrumenters, Dyninst can instrument at any time in the execution continuum, from static Instrumentation (binary rewriting) to instrumenting actively executing code (dynamic Instrumentation). Furthermore, we allow users to modify or remove Instrumentation at any time, with such modifications taking immediate effect. Our analysis techniques allow us to insert new code without modifying uninstrumented code; as a result, all uninstrumented code executes at native speed. We demonstrate that our techniques provide this collection of capabilities while imposing similar or lower overhead than other widely used instrumenters.

  • PASTE – Anywhere, any-time binary Instrumentation
    Proceedings of the 10th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools – PASTE '11, 2011
    Co-Authors: Andrew R Bernat, Barton P Miller
    Abstract:

    The Dyninst binary Instrumentation and analysis framework distinguishes itself from other binary Instrumentation tools through its abstract, machine independent interface; its emphasis on anywhere, any-time binary Instrumentation; and its low overhead that is proportional to the number of instrumented locations. Dyninst represents the program in terms of familiar control flow structures such as functions, loops, and basic blocks, and users manipulate these representations to insert Instrumentation anywhere in the binary. We use graph transformation techniques to insure that this Instrumentation executes when desired even when instrumenting highly optimized (or malicious) code that other instrumenters cannot correctly instrument. Unlike other binary instrumenters, Dyninst can instrument at any time in the execution continuum, from static Instrumentation (binary rewriting) to instrumenting actively executing code (dynamic Instrumentation). Furthermore, we allow users to modify or remove Instrumentation at any time, with such modifications taking immediate effect. Our analysis techniques allow us to insert new code without modifying uninstrumented code; as a result, all uninstrumented code executes at native speed. We demonstrate that our techniques provide this collection of capabilities while imposing similar or lower overhead than other widely used instrumenters.

  • PPOPP – Dynamic Instrumentation of threaded applications
    Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming – PPoPP '99, 1999
    Co-Authors: Barton P Miller, Oscar Naim
    Abstract:

    The use of threads is becoming commonplace in both sequential and parallel programs. This paper describes our design and initial experience with non-trace based performance Instrumentation techniques for threaded programs. Our goal is to provide detailed performance data while maintaining control of Instrumentation costs. We have extended Paradyn’s dynamic Instrumentation (which can instrument programs without recompiling or relinking) to handle threaded programs.Controlling Instrumentation costs means efficient Instrumentation code and avoiding locks in the Instrumentation. Our design is based on low contention data structures. To associate performance data with individual threads, we have all threads share the same Instrumentation code and assign each thread with its own private copy of performance counters or timers. The asynchrony in a threaded program poses a major challenge to dynamic Instrumentation. To implement time-based metrics on a per-thread basis, we need to instrument thread context switches, which can cause Instrumentation code to interleave. Interleaved Instrumentation can not only corrupt performance data, but can also cause a scenario we call self-deadlock where an Instrumentation code deadlocks a thread. We introduce thread-conscious locks to avoid self-deadlock, and per-thread virtual CPU timers to reduce the chance of interleaved Instrumentation accessing the same performance counter or timer, and to reduce the number of expensive timer calls at thread context switches.Our initial implementation is on SPARC Solaris 2.5 and 2.6 including multiprocessor Sun UltraSPARC Enterprise machines. We tested our tool on large multithreaded applications, including the Java Virtual Machine (JVM). We show how our new techniques helped us to speed up a Java graphics native method by 42% and consequently increase by 24% the amount of work that can be done in unit time in a game applet.

Andrew R Bernat – One of the best experts on this subject based on the ideXlab platform.

  • anywhere any time binary Instrumentation
    Workshop on Program Analysis For Software Tools and Engineering, 2011
    Co-Authors: Andrew R Bernat, Barton P Miller
    Abstract:

    The Dyninst binary Instrumentation and analysis framework distinguishes itself from other binary Instrumentation tools through its abstract, machine independent interface; its emphasis on anywhere, any-time binary Instrumentation; and its low overhead that is proportional to the number of instrumented locations. Dyninst represents the program in terms of familiar control flow structures such as functions, loops, and basic blocks, and users manipulate these representations to insert Instrumentation anywhere in the binary. We use graph transformation techniques to insure that this Instrumentation executes when desired even when instrumenting highly optimized (or malicious) code that other instrumenters cannot correctly instrument. Unlike other binary instrumenters, Dyninst can instrument at any time in the execution continuum, from static Instrumentation (binary rewriting) to instrumenting actively executing code (dynamic Instrumentation). Furthermore, we allow users to modify or remove Instrumentation at any time, with such modifications taking immediate effect. Our analysis techniques allow us to insert new code without modifying uninstrumented code; as a result, all uninstrumented code executes at native speed. We demonstrate that our techniques provide this collection of capabilities while imposing similar or lower overhead than other widely used instrumenters.

  • PASTE – Anywhere, any-time binary Instrumentation
    Proceedings of the 10th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools – PASTE '11, 2011
    Co-Authors: Andrew R Bernat, Barton P Miller
    Abstract:

    The Dyninst binary Instrumentation and analysis framework distinguishes itself from other binary Instrumentation tools through its abstract, machine independent interface; its emphasis on anywhere, any-time binary Instrumentation; and its low overhead that is proportional to the number of instrumented locations. Dyninst represents the program in terms of familiar control flow structures such as functions, loops, and basic blocks, and users manipulate these representations to insert Instrumentation anywhere in the binary. We use graph transformation techniques to insure that this Instrumentation executes when desired even when instrumenting highly optimized (or malicious) code that other instrumenters cannot correctly instrument. Unlike other binary instrumenters, Dyninst can instrument at any time in the execution continuum, from static Instrumentation (binary rewriting) to instrumenting actively executing code (dynamic Instrumentation). Furthermore, we allow users to modify or remove Instrumentation at any time, with such modifications taking immediate effect. Our analysis techniques allow us to insert new code without modifying uninstrumented code; as a result, all uninstrumented code executes at native speed. We demonstrate that our techniques provide this collection of capabilities while imposing similar or lower overhead than other widely used instrumenters.

  • scalable dynamic binary Instrumentation for blue gene l
    ACM Sigarch Computer Architecture News, 2005
    Co-Authors: Martin Schulz, Andrew R Bernat, D Ahn, Bronis R. De Supinski, Gregory L. Lee, Barry Rountree
    Abstract:

    Dynamic binary Instrumentation for performance analysis on new, large scale architectures such as the IBM Blue Gene/L system (BG/L) poses new challenges. Their scale—with potentially hundreds of thousands of compute nodes—requires new, more scalable mechanisms to deploy and to organize binary Instrumentation and to collect the resulting data gathered by the inserted probes. Further, many of these new machines don’t support full operating systems on the compute nodes; rather, they rely on light-weight custom compute kernels that do not support daemon-based implementations.We describe the design and current status of a new implementation of the DPCL (Dynamic Probe Class Library) API for BG/L. DPCL provides an easy to use layer for dynamic Instrumentation on parallel MPI applications based on the DynInst dynamic Instrumentation mechanism for sequential platforms. Our work includes modifying DynInst to control Instrumentation from remote I/O nodes and porting DPCL’s communication to use MRNet, a scalable data reduction network for collecting performance data. We describe extensions to the DPCL API that support Instrumentation of task subsets and aggregation of collected performance data. Overall, our implementation provides a scalable infrastructure that provides efficient binary Instrumentation on BG/L.

Francinne M Rosa – One of the best experts on this subject based on the ideXlab platform.

  • manual and rotary Instrumentation techniques for root canal preparation in primary molars
    Dentistry 3000, 2014
    Co-Authors: Francinne M Rosa, Adriana Modesto, Italo M Faracojunior
    Abstract:

    Introduction: Although rotary Instrumentation has been widely studied in permanent dentition, it is a rather new field of study concerning primary teeth. Purpose: We aimed to evaluate apical displacement and time needed for Instrumentation of root canals of primary molars by manual and rotary techniques. Materials and Methods: Root canals of 144 extracted first and second primary maxillary molars were randomly divided into 2 groups: Imanual Instrumentation (K -files); II- rotary Instrumentation (K3 Rotary System®). The canals were radiographed with pathfinding files in place, prepared by both techniques, and Instrumentation time was recorded. After preparation, root canals were radiographed again with pathfinding files in place. To analyze the degree of apical displacement, digital images were superimposed using the Adobe Photoshop® software. Results: Mean apical displacement (0.70 mm) in the manual Instrumentation group was not statistically different from that in the rotary Instrumentation group (0.79 mm). However, mean time for root canal preparation was significantly shorter using the rotary system (128.0 s) than using the manual system (174.0 s) (p<0.05). Conclusions: The use of rotary Instrumentation in pediatric dentdentistry is feasible, offering time -saving advantages in root canal preparation.

  • Manual and rotary Instrumentation techniques for root canal preparation in primary molars
    Dentistry 3000, 2014
    Co-Authors: Francinne M Rosa, Adriana Modesto, Italo M. Faraco-junior
    Abstract:

    Introduction: Although rotary Instrumentation has been widely studied in permanent dentition, it is a rather new field of study concerning primary teeth. Purpose: We aimed to evaluate apical displacement and time needed for Instrumentation of root canals of primary molars by manual and rotary techniques. Materials and Methods: Root canals of 144 extracted first and second primary maxillary molars were randomly divided into 2 groups: Imanual Instrumentation (K -files); II- rotary Instrumentation (K3 Rotary System®). The canals were radiographed with pathfinding files in place, prepared by both techniques, and Instrumentation time was recorded. After preparation, root canals were radiographed again with pathfinding files in place. To analyze the degree of apical displacement, digital images were superimposed using the Adobe Photoshop® software. Results: Mean apical displacement (0.70 mm) in the manual Instrumentation group was not statistically different from that in the rotary Instrumentation group (0.79 mm). However, mean time for root canal preparation was significantly shorter using the rotary system (128.0 s) than using the manual system (174.0 s) (p

Italo M Faracojunior – One of the best experts on this subject based on the ideXlab platform.

  • manual and rotary Instrumentation techniques for root canal preparation in primary molars
    Dentistry 3000, 2014
    Co-Authors: Francinne M Rosa, Adriana Modesto, Italo M Faracojunior
    Abstract:

    Introduction: Although rotary Instrumentation has been widely studied in permanent dentition, it is a rather new field of study concerning primary teeth. Purpose: We aimed to evaluate apical displacement and time needed for Instrumentation of root canals of primary molars by manual and rotary techniques. Materials and Methods: Root canals of 144 extracted first and second primary maxillary molars were randomly divided into 2 groups: Imanual Instrumentation (K -files); II- rotary Instrumentation (K3 Rotary System®). The canals were radiographed with pathfinding files in place, prepared by both techniques, and Instrumentation time was recorded. After preparation, root canals were radiographed again with pathfinding files in place. To analyze the degree of apical displacement, digital images were superimposed using the Adobe Photoshop® software. Results: Mean apical displacement (0.70 mm) in the manual Instrumentation group was not statistically different from that in the rotary Instrumentation group (0.79 mm). However, mean time for root canal preparation was significantly shorter using the rotary system (128.0 s) than using the manual system (174.0 s) (p<0.05). Conclusions: The use of rotary Instrumentation in pediatric dentistry is feasible, offering time -saving advantages in root canal preparation.

Italo M. Faraco-junior – One of the best experts on this subject based on the ideXlab platform.

  • Manual and rotary Instrumentation techniques for root canal preparation in primary molars
    Dentistry 3000, 2014
    Co-Authors: Francinne M Rosa, Adriana Modesto, Italo M. Faraco-junior
    Abstract:

    Introduction: Although rotary Instrumentation has been widely studied in permanent dentition, it is a rather new field of study concerning primary teeth. Purpose: We aimed to evaluate apical displacement and time needed for Instrumentation of root canals of primary molars by manual and rotary techniques. Materials and Methods: Root canals of 144 extracted first and second primary maxillary molars were randomly divided into 2 groups: Imanual Instrumentation (K -files); II- rotary Instrumentation (K3 Rotary System®). The canals were radiographed with pathfinding files in place, prepared by both techniques, and Instrumentation time was recorded. After preparation, root canals were radiographed again with pathfinding files in place. To analyze the degree of apical displacement, digital images were superimposed using the Adobe Photoshop® software. Results: Mean apical displacement (0.70 mm) in the manual Instrumentation group was not statistically different from that in the rotary Instrumentation group (0.79 mm). However, mean time for root canal preparation was significantly shorter using the rotary system (128.0 s) than using the manual system (174.0 s) (p