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Indexed at: search.filters.indexed.TR DizinSubject: search.filters.subject.Artificial intelligence

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    Access pattern-aware data placement for hybrid DRAM/NVM
    (TUBITAKScientific and Technical Research Council Turkey, 2017) Department of Computer Engineering; Erten, Didem Unat; Faculty Member; Department of Computer Engineering; College of Engineering; 219274
    in recent years, increased interest in data-centric applications has led to an increasing demand for large capacity memory systems. Nonvolatile memory (NVM) technologies enable new opportunities in terms of process-scaling and energy consumption, and have become an attractive memory technology that serves as a secondary memory at low cost. However, NVM has certain disadvantages for write references, due to its high dynamic energy consumption for writes and low bandwidth compared to DRaM writes. in this paper, we propose an access-aware placement of objects in the application code for two types of memories. Given the desired power savings and acceptable performance loss, our placement algorithm suggests candidate variables for NVM. We present an evaluation of the proposed technique on two applications and study the energy and performance consequences of different placements.
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    PublicationOpen Access
    BlockSim-Net: a network-based blockchain simulator
    (TÜBİTAK, 2022) Ramachandran, Prashanthi; Agrawal, Nandini; Department of Computer Engineering; Biçer, Osman; Küpçü, Alptekin; Faculty Member; Department of Computer Engineering; College of Engineering; Graduate School of Sciences and Engineering; N/A; 168060
    Since its proposal by Eyal and Sirer (CACM '13), selfish mining attacks on proof-of-work blockchains have been studied extensively. The main body of this research aims at both studying the extent of its impact and defending against it. Yet, before any practical defense is deployed in a real world blockchain system, it needs to be tested for security and dependability. However, real blockchain systems are too complex to conduct any test on or benchmark the developed protocols. Instead, some simulation environments have been proposed recently, such as BlockSim (Maher et al., SIGMETRICS Perform. Eval. Rev. '19), which is a modular and easy-to-use blockchain simulator. However, BlockSim's structure is insufficient to capture the essence of a real blockchain network, as the simulation of an entire network happens over a single CPU. Such a lack of decentralization can cause network issues such as propagation delays being simulated in an unrealistic manner. In this work, we propose BlockSim-Net, a modular, efficient, high performance, distributed, network-based blockchain simulator that is parallelized to better reflect reality in a blockchain simulation environment.