Locality-aware adaptive grain signatures for Transactional Memories

Choi, Woojin; Draper, J.

doi:10.1109/ipdps.2010.5470476

Cited by 11 publications

(7 citation statements)

References 26 publications

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“…However, if the transaction needs to abort eventually, delaying the aborting cause the transaction to either take longer to recover (Intruder) or stall peer transactions longer (SSCA2). The results of these two workloads echo the findings in [10] that early termination of ultimately conflicting transactions could sometimes improve performance. Nonetheless, the majority of the workloads in our evaluation do benefit from the increased concurrency.…”

Section: Reduction In Network Energysupporting

confidence: 75%

Consolidated conflict detection for hardware transactional memory

Zhao

Draper

2014

Proceedings of the 23rd International Conference on Parallel Architectures and Compilation

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Hardware Transactional Memory (HTM) promises to ease multithreaded parallel programming with uncompromised performance. Microprocessors supporting HTM implement a conflict detection mechanism to detect data access conflicts between transactions. Understanding the on-chip network bandwidth utilization of such mechanisms is important as the energy and latency cost of routing packets across the chip is growing alarmingly. We investigate the communication characteristics of a typical conflict detection mechanism. A variety of traffic overheads are identified, which accounts for a combined 56% of the total transactional traffic in a wide spectrum of applications. To combat this problem, we propose C2D (Consolidated Conflict Detection), a novel micro-architectural technique to consolidate conflict detection to a logically central (but physically distributed) agent to reduce the bandwidth utilization of conflict detection. Full system evaluation shows that the proposed technique, if applied to conventional eager conflict detection, can reduce 35% of the traffic and hence 27% of the network energy. The consolidated eager conflict detection generates less traffic than a lazy conflict detection scheme thereby closing the gap between bandwidth utilization of eager and lazy conflict detection.

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Section: Reduction In Network Energysupporting

confidence: 75%

Consolidated conflict detection for hardware transactional memory

Zhao

Draper

2014

Proceedings of the 23rd International Conference on Parallel Architectures and Compilation

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“…Recently, Choi et al [7] proposed adaptive grain signatures, which keep the history of transaction aborts and dynamically changes the input bit range to the hash functions based on the abort history. The aim of this design is to reduce the number of false positives that harm the execution performance.…”

Section: Background and Related Workmentioning

confidence: 99%

Multiset signatures for transactional memory

Quislant

Gutiérrez

Plata

et al. 2011

Proceedings of the International Conference on Supercomputing

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Transactional Memory (TM) systems must record the memory locations read and written (read and write sets) by concurrent transactions in order to detect conflicts. Some TM implementations use signatures for this purpose, which summarize read and write sets in bounded hardware at the cost of false positives (detection of non-existing conflicts).Read/write signatures are usually implemented as two separate Bloom filters with the same size. In contrast, transactions usually exhibit read/write sets of uneven cardinality, where read sets use to be larger than write sets. Thus, the read filter populates earlier than the write one and, consequently the read signature false positive rate may be high while the write filter has still a low occupation.In this paper, a multiset signature design is proposed which records both the read and write sets in the same Bloom filter without adding significant hardware complexity. Several designs of multiset signatures are analyzed and evaluated. New problems arise related to hardware complexity and the existence of cross false positives, i.e. new false positives coming from the fact that both sets share the same filter. Additionally, multiset signatures are enhanced using locality-sensitive hashing, proposed by the authors in a previous work. Experimental results show that the multiset approach is able to reduce the false positive rate and improve the execution performance in most of the tested codes, without increasing the required hardware area in a noticeable amount.

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“…If conflicting transactions contain spatial locality among their data accesses (memory accesses b and i in Figure 2), we can harvest good positives with coarser-grain signatures. A more detailed analysis of a good positive distribution for STAMP benchmarks [8] can be found in [9].…”

Section: A Good False Postives Vs Bad False Positivesmentioning

confidence: 99%

“…The maximum speedup of a TM system with AGSig-C is 75.07%, with an average of 17.19%, over a TM system using PBX. A more detailed analysis of performance can be found elsewhere [9].…”

Section: Performance Evaluationmentioning

confidence: 99%

Implementation of adaptive grain signatures for transactional memories

Choi

Kang

Kwon

et al. 2010

Proceedings of 2010 IEEE International Symposium on Circuits and Systems

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Abstract-Hardware signatures for Transactional Memory (TM) systems have been proposed as an efficient mechanism for conflict detection, an essential element in TM for maintaining correctness. A signature misses no conflicts, but could falsely declare conflicts even when no true conflict exists (false positives). In this paper, we show that some false positives can be helpful to the performance by triggering the early abortion of a transaction which would encounter a true conflict later anyway. We propose an adaptive grain signature to improve TM performance by dynamically changing the range of address keys based on the history. With architecture-level simulation and Verilog HDL implementation, we demonstrate that a TM system with our design frequently outperforms baseline TM systems, with marginal area overhead.

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Locality-aware adaptive grain signatures for Transactional Memories

Cited by 11 publications

References 26 publications

Consolidated conflict detection for hardware transactional memory

Consolidated conflict detection for hardware transactional memory

Multiset signatures for transactional memory

Implementation of adaptive grain signatures for transactional memories

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