Row-hammering flips bits in a victim DRAM row by frequently activating its adjacent rows, compromising DRAM integrity. Several studies propose to prevent row-hammering by counting the number of activates to a DRAM row and refreshing the corresponding victim rows before the count surpasses a rowhammer threshold. However, these approaches either incur a significant area overhead or a large number of additional activations (ACT) that could degrade the system performance. In this paper, we propose CAT-TWO, a time-window-optimized version of the existing Counter-based Adaptive Tree (CAT) scheme for row-hammer prevention. We first ensure that the victim rows are always refreshed at the last level of the tree without counter overflow by configuring the threshold and the number of CAT-TWO counters based on the fact that the maximum number of ACTs is limited within the refresh window. We further reduce the size and latency of CAT-TWO by applying high-radix rank-level CAT-TWO with multiple tree roots. CAT-TWO incurs less than 0.7% energy overhead on a baseline DDR4 DRAM device, and generates less than 0.03% additional ACTs to refresh victim rows in the worst case, which hardly affects system performance. INDEX TERMS DRAM chips, DRAM reliability, row-hammering.
BackgroundControlling the fate of mesenchymal stems cells (MSCs) including proliferation, migration and differentiation has recently been studied by many researchers in the tissue engineering field. Especially, recruitment of stem cells to injury sites is the first and crucial step in tissue regeneration. Although significant progress has been made in the chemotactic migration of MSCs, MSC migration in three dimensional environments remains largely unknown. We developed a 3D hydrogel-based microfluidic-device to study the migration behavior of human MSCs in the presence of stromal-cell derived factor-1α (SDF-1α), interleukin 8 (IL-8) and Substance P (SP) which have been utilized as chemoattractant candidates of human mesenchymal stem cells (hMSCs).ResultsWe systematically investigated the chemotactic migration behaviors of hMSCs and their responses to SDF-1α, IL-8, and SP. SDF-1α was shown to be the most fascinating chemoattractant candidate among those factors at a certain time point. We also found that each chemokine showed different chemoattractant abilities according to their concentration. In the case of SP, this factor showed chemokinesis not chemotaxis. Especially at a 7–8 × 10−8 M concentration range, the chemokinesis ability driven by SP was further increased. The data suggest that some factors at the optimal concentration exhibit chemokinesis or chemotaxis in a 3D hydrogel-based microfluidic device.ConclusionIn this study on chemotaxis and chemokinesis of hMSCs, the system parameters such as chemokine concentration, system stability, and 2D or 3D microenvironment are critically important to obtain meaningful results.
Homomorphic Encryption (HE) draws a significant attention as a privacy-preserving way for cloud computing because it allows computation on encrypted messages called ciphertexts. Among numerous HE schemes proposed, HE for Arithmetic of Approximate Numbers (HEAAN) is rapidly gaining popularity across a wide range of applications as it supports messages that can tolerate approximate computation with no limit on the number of arithmetic operations applicable to the ciphertexts. A critical shortcoming of HE is the high computation complexity of ciphertext arithmetic; especially, HE multiplication (HE Mul) is more than 10,000 times slower than the corresponding multiplication between unencrypted messages. This leads to a large body of HE acceleration studies including ones exploiting FPGAs; however, those did not conduct a rigorous analysis of computational complexity and data access patterns of HE Mul. Moreover, the proposals mostly focused on designs with small parameter sizes, making it difficult to accurately estimate the performance of the HE accelerators in conducting a series of complex arithmetic operations. In this paper, we first describe how HE Mul of HEAAN is performed in a manner friendly to non-crypto experts. Then we conduct a disciplined analysis on its computational and memory-access characteristics, through which we (1) extract parallelism in the key functions composing HE Mul and (2) demonstrate how to effectively map the parallelism to the popular parallel processing platforms, CPUs and GPUs, by applying a series of optimizations such as transposing matrices and pinning data to threads. This leads to the performance improvement of HE Mul on a CPU and a GPU by 2.06× and 4.05×, respectively, over the reference HEAAN running on a CPU with 24 threads.
INDEX TERMSComputer applications, Computer architecture, Cryptography, Multicore processing I. INTRODUCTION
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