2012
DOI: 10.1002/cpe.2866
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On the design of energy‐efficient hardware transactional memory systems

Abstract: SUMMARYTransactional memory is currently being advocated as a promising alternative to lock‐based synchronization because it simplifies multithreaded programming. In this way, future many‐core chip multiprocessor architectures may need to provide hardware support for transactional memory. On the other hand, energy consumption constitutes nowadays a first class consideration in multicore processor designs. In this work, we characterize the performance and energy consumption of two well‐known hardware transactio… Show more

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Cited by 6 publications
(3 citation statements)
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References 27 publications
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“…In both [21,20] the authors assess the behaviour of different HTM implementations via simulation (the latter focusing on embedded systems). The approach was also taken by [2], where the power consumption of one STM was studied via simulation.…”
Section: Related Workmentioning
confidence: 99%
“…In both [21,20] the authors assess the behaviour of different HTM implementations via simulation (the latter focusing on embedded systems). The approach was also taken by [2], where the power consumption of one STM was studied via simulation.…”
Section: Related Workmentioning
confidence: 99%
“…Ballga et al [4] have described analysis and technology for energy consumption of data throughput in network's like DSL, HFC networks, passive optical networks, point to point optical systems, W-CDMA, WiMAX. Gaona et al [5] have given the design of energy-efficient in hardware transactional memory systems. Chiaraviglio et al [6] have given the model based energy consumption mechanism such as device architecture and load for networks.…”
Section: Related Workmentioning
confidence: 99%
“…In addition, memory energy management is challenging in the context of servers with modern DRAM technologies. According to the recent studies [6,7], main memory in massive server platforms accounts for up to 40% of server energy which is comparable to or slightly higher than the energy consumption contribution of CPUs. In cloud datacenters, the fraction attributable to memory accesses may be even higher, because resource virtualization technology will introduce extra energy…”
Section: Introductionmentioning
confidence: 99%