Analysis and Tracing of Applications Based on Software Transactional Memory on Multicore Architectures

Abstract

International audienceTransactional Memory (TM) is a new programming paradigm that offers an alternative to traditional lock-based concurrency mechanisms. It offers a higher-level programming interface and promises to greatly simplify the development of correct concurrent applications on multicore architectures. However, simplicity often comes with an important performance deterioration and given the variety of TM implementations it is still a challenge to know what kind of applications can really take advantage of TM. In order to gain some insight on these issues, helping developers to understand and improve the performance of TM applications, we propose a generic approach for collecting and tracing relevant information about transactions. Our solution can be applied to different Software Transactional Memory (STM) libraries and applications as it does not modify neither the target application nor the STM library source codes. We show that the collected information can be helpful in order to comprehend the performance of TM applications

Evaluating the Impact of Transactional Characteristics on the Performance of Transactional Memory Applications

“…To evaluate the results, they implemented a tool to visualize the collected transactional information. Castro et al [11] proposed an approach for collecting and tracing relevant information about transactions. It was based on the Linux dynamic linking mechanism, which traces events about transactions.…”

“…Unlike [12], [13], this approach has the advantage of using a larger variety of STM systems without modifying the source codes. Moreover, it does not add any overhead, as opposed to the works presented in [11], [14] which may modify the behavior of the applications due to extra operations to collect data.…”

“…Although there have been advances in the area, TM is still under research due to unanswered questions. As discussed in [11], it is still challenging to know what kind of applications can really take advantage of TM. Finally, as identified by [12], it is essential to investigate the reasons why some TM applications present low performance and how to identify in advance which applications can benefit from this model.…”

“…However, TM applications must be analyzed carefully to identify the most relevant characteristics that may help to improve their overall performance. As an opportunity for the future, we intend to extend this work using some tracing mechanisms as proposed in [11]. Moreover, we intend to study the impact of the TM characteristics on the performance of TM applications when executed on a real HTM processor such as the Intel Haswell.…”