• Journal of Information Processing Systems
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• v.14 no.2
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• pp.499-509
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• 2018

Recently, hybrid transactional memory (HyTM) has gained much interest from researchers because it combines the advantages of hardware transactional memory (HTM) and software transactional memory (STM). To provide the concurrency control of transactions, the existing HyTM-based studies use a bloom filter. However, they fail to overcome the typical false positive errors of a bloom filter. Though the existing studies use a global lock, the efficiency of global lock-based memory allocation is significantly low in multi-core environment. In this paper, we propose an efficient hybrid transactional memory scheme using near-optimal retry computation and sophisticated memory management in order to efficiently process transactions in multi-core environment. First, we propose a near-optimal retry computation algorithm that provides an efficient HTM configuration using machine learning algorithms, according to the characteristic of a given workload. Second, we provide an efficient concurrency control for transactions in different environments by using a sophisticated bloom filter. Third, we propose a memory management scheme being optimized for the CPU cache line, in order to provide a fast transaction processing. Finally, it is shown from our performance evaluation that our HyTM scheme achieves up to 2.5 times better performance by using the Stanford transactional applications for multi-processing (STAMP) benchmarks than the state-of-the-art algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1041-1049
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• 2012

The transactional memory was proposed to solve the problems of the conventional lock-based synchronization methods in the shared memory multiprocessor system. Various implementation methods for putting the high performance transactional memory to practical use have been continuously studied. However, these studies focus only on the commercialization and performance enhancement of the transactional memory. Besides, there have been few studies to analyze the system overhead of the transactional memory according to the conflict management policy. Thus this paper classifies hardware transactional memory, which is one kind of transactional memories, into four types according to the conflict management policy, and then compares and analyzes their performance and system bus traffic through their modeling and simulation. In addition, the most effective conflict management policy for the hardware transactional memory is presented through these comparison and analysis.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.466-472
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• 2017

Hardware Transactional Memory (HTM) has greatly changed the parallel programming paradigm for transaction processing. Since Intel has recently proposed Transactional Synchronization Extension (TSX), a number of studies based on HTM have been conducted. However, the existing studies support conflict prediction for a single cause of the transaction processing and provide a standardized TSX environment for all workloads. To solve the problems, we propose an efficient hardware transactional memory scheme for processing transactions in multi-core in-memory environment. First, the proposed scheme determines whether to use Software Transactional Memory (STM) or the serial execution as a fallback path of HTM by using a prediction matrix to collect the information of previously executed transactions. Second, the proposed scheme performs efficient transaction processing according to the characteristic of a given workload by providing a retry policy based on machine learning algorithms. Finally, through the experimental performance evaluation using Stanford transactional applications for multi-processing (STAMP), the proposed scheme shows 10~20% better performance than the existing schemes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.72-79
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• 2011

The importance of parallel programming seriously emerges ever since the modern microprocessor architecture has been shifted to the multi-core system. Transactional Memory has been proposed to address synchronization which is usually implemented by using locks. However, the lock based synchronization method reduces the parallelism and has the possibility of causing deadlock. In this paper, we propose an efficient method to utilize transactional memory for the situation which has high contention. The proposed idea is based on the theoretical analysis and it is verified with simulation results. The simulation environment has been implemented using HTM(Hardware Transactional Memory) systems. We also propose a model of the dining philosopher problem to discuss the efficient resource management using the transactional memory technique.

• The KIPS Transactions:PartA
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• v.18A no.1
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• pp.19-24
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• 2011

As era of multi-core processors has arrived, transactional memory has been considered as an effective method to achieve easy and fast multi-threaded programming. Various hardware transactional memory systems such as UTM, VTM, FastTM, LogTM, and LogTM-SE, have been introduced in order to implement high-performance multi-core processors. Especially, LogTM-SE has provided study performance with an efficient memory management policy and a practical thread scheduling method through conflict detection based on signatures. However, increasing number of cores on a processor imposes the hardware complexity for signature processing. This causes overall performance degradation due to the heavy workload on signature comparison. In this paper, we propose a new architecture of multiple signature comparison to improve conflict detection of signature based transactional memory systems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.1-8
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• 2011

Traditional transactional memory systems are no longer able to guarantee the performance of diverse applications with overflowed transactions since there is the drawback that tracking the data for logging is difficult. Especially, this mechanism has a disadvantage of increasing communication delay for sustaining the state which is required to detect the conflict on the overflowed transactions from the first level cache in the transactional memory systems. To address this point, we have focused on the cache architecture of the systems to reduce the overhead caused by overflows and cache misses. In this paper, we present Supportive Cache which reduces additional overhead during transactions. Supportive Cache performs a parallel look-up with L1 private cache and uses the same replacement policy as L1 private cache. We evaluate the performance of the proposed design by comparing LogTM-SE with and without Supportive Cache. The simulation results show that our system improves the performance by 37% on average, compared to the original LogTM-SE which uses the same hardware resource.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.49-61
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• 2017

Transactional Memory (TM) has greatly changed the parallel programming paradigm for transaction processing and is classified into STM, HTM, HyTM according to hardware or software frameworks. However, the existing studies have a problem that they provide static retry policy for all workloads. To solve the problems, we propose an hybrid transactional memory scheme using sampling-based adaptive retry policy in multi-core environment. First, the proposed scheme determines whether to use STM or HTM according to the characteristic of a transaction. Otherwise, it executes HTM and STM concurrently by using a bloom filter. Second, the proposed scheme provides adaptive retry policy for HTM according to the characteristic of transactions in each workload. Finally, through the experimental performance evaluation using STAMP, the proposed scheme shows 10~20% better performance than the existing schemes.

• Journal of KIISE
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• v.42 no.4
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• pp.442-450
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• 2015

This paper proposes a method for reducing false conflicts in signature-based eager hardware transactional memory (HTM). The method tracks the information on all cache blocks that are accessed by a transaction. If the information provides evidence that there are no conflicts for a given transactional request from another core, the method prevents the occurrence of a false conflict by forcing the HTM to ignore the decision based on the signature. The method is very effective in reducing false conflicts and the associated unnecessary transaction stalls and aborts, and can be used to improve the performance of the multicore processor that implements the signature-based eager HTM. When running the STAMP benchmark on a 16-core processor that implements the LogTM-SE, the increased speed (decrease in execution time) achieved with the use of the method is 20.6% on average.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.3-4
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• 2016

멀티스레드 프로그램의 수행 중에 발생할 수 있는 자료경합은 프로그래머가 의도하지 않은 비결정적 수행으로 인해 신뢰할 수 없는 프로그램의 결과를 발생시킨다. 이러한 자료경합의 디버깅을 위해서 시간 및 자원적 비용이 과도하게 발생하기 때문에 프로그램의 수행 중에 이를 용인하고 치유하는 것이 중요하다. 본 논문은 멀티스레드 프로그램을 대상으로 소프트웨어 트랜잭셔널 메모리(STM)를 사용하여 공유변수에 대한 트랜잭션 영역을 설정하고 공유변수에 대한 이벤트 충돌 유형에 따른 자료경합 치유기법을 설계한다. 최종적으로는 프로그램 수행 중에 자료경합을 치유하는 기법의 실현가능성을 확인한다.

• International Journal of Contents
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• v.12 no.1
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• pp.60-64
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• 2016

As new applications of cloud data management system (CDMS) such as online games, cooperation edit, social network, and so on, are increasing, transaction processing capabilities for CDMS are required. Several transaction processing methods for cloud data management system (CDMS) have been proposed. However, existing transaction processing methods have some problems. Some of them provide limited transaction processing capabilities. Some of them are hard to be integrated with existing CDMSs. In this paper, we proposed a new concurrency control method to support transaction processing capability for CDMS to solve these problems. The proposed method was designed and implemented based on Spark, an in-memory distributed processing framework. It uses RDD (Resilient Distributed Dataset) model to provide fault tolerant to data in the main memory. In our proposed method, database stored in CDMS is loaded to main memory managed by Spark. The loaded data set is then transformed to RDD. In addition, we proposed a multi-version concurrency control method through immutable characteristics of RDD. Finally, we performed experiments to show the feasibility of the proposed method.