Optimization of micropillar sequences for fluid flow sculpting

Inertial fluid flow deformation around pillars in a microchannel is a new method for controlling fluid flow. Sequences of pillars have been shown to produce a rich phase space with a wide variety of flow transformations. Previous work has successfully demonstrated manual design of pillar sequences to achieve desired transformations of the flow cross-section, with experimental validation. However, such a method is not ideal for seeking out complex sculpted shapes as the search space quickly becomes too large for efficient manual discovery. We explore fast, automated optimization methods to solve this problem. We formulate the inertial flow physics in microchannels with different micropillar configurations as a set of state transition matrix operations. These state transition matrices are constructed from experimentally validated streamtraces. This facilitates modeling the effect of a sequence of micropillars as nested matrix-matrix products, which have very efficient numerical implementations. With this new forward model, arbitrary micropillar sequences can be rapidly simulated with various inlet configurations, allowing optimization routines quick access to a large search space. We integrate this framework with the genetic algorithm and showcase its applicability by designing micropillar sequences for various useful transformations. We computationally discover micropillar sequences for complex transformations that are substantially shorter than manually designed sequences. We also determine sequences for novel transformations that were difficult to manually design. Finally, we experimentally validate these computational designs by fabricating devices and comparing predictions with the results from confocal microscopy

Improving DRAM Performance by Parallelizing Refreshes with Accesses

Modern DRAM cells are periodically refreshed to prevent data loss due to leakage. Commodity DDR DRAM refreshes cells at the rank level. This degrades performance significantly because it prevents an entire rank from serving memory requests while being refreshed. DRAM designed for mobile platforms, LPDDR DRAM, supports an enhanced mode, called per-bank refresh, that refreshes cells at the bank level. This enables a bank to be accessed while another in the same rank is being refreshed, alleviating part of the negative performance impact of refreshes. However, there are two shortcomings of per-bank refresh. First, the per-bank refresh scheduling scheme does not exploit the full potential of overlapping refreshes with accesses across banks because it restricts the banks to be refreshed in a sequential round-robin order. Second, accesses to a bank that is being refreshed have to wait. To mitigate the negative performance impact of DRAM refresh, we propose two complementary mechanisms, DARP (Dynamic Access Refresh Parallelization) and SARP (Subarray Access Refresh Parallelization). The goal is to address the drawbacks of per-bank refresh by building more efficient techniques to parallelize refreshes and accesses within DRAM. First, instead of issuing per-bank refreshes in a round-robin order, DARP issues per-bank refreshes to idle banks in an out-of-order manner. Furthermore, DARP schedules refreshes during intervals when a batch of writes are draining to DRAM. Second, SARP exploits the existence of mostly-independent subarrays within a bank. With minor modifications to DRAM organization, it allows a bank to serve memory accesses to an idle subarray while another subarray is being refreshed. Extensive evaluations show that our mechanisms improve system performance and energy efficiency compared to state-of-the-art refresh policies and the benefit increases as DRAM density increases.Comment: The original paper published in the International Symposium on High-Performance Computer Architecture (HPCA) contains an error. The arxiv version has an erratum that describes the error and the fix for i

RowHammer: Reliability Analysis and Security Implications

As process technology scales down to smaller dimensions, DRAM chips become more vulnerable to disturbance, a phenomenon in which different DRAM cells interfere with each other's operation. For the first time in academic literature, our ISCA paper exposes the existence of disturbance errors in commodity DRAM chips that are sold and used today. We show that repeatedly reading from the same address could corrupt data in nearby addresses. More specifically: When a DRAM row is opened (i.e., activated) and closed (i.e., precharged) repeatedly (i.e., hammered), it can induce disturbance errors in adjacent DRAM rows. This failure mode is popularly called RowHammer. We tested 129 DRAM modules manufactured within the past six years (2008-2014) and found 110 of them to exhibit RowHammer disturbance errors, the earliest of which dates back to 2010. In particular, all modules from the past two years (2012-2013) were vulnerable, which implies that the errors are a recent phenomenon affecting more advanced generations of process technology. Importantly, disturbance errors pose an easily-exploitable security threat since they are a breach of memory protection, wherein accesses to one page (mapped to one row) modifies the data stored in another page (mapped to an adjacent row).Comment: This is the summary of the paper titled "Flipping Bits in Memory Without Accessing Them: An Experimental Study of DRAM Disturbance Errors" which appeared in ISCA in June 201

A comparative transcriptome analysis of the novel obligate methanotroph Methylomonas sp. DH-1 reveals key differences in transcriptional responses in C1 and secondary metabolite pathways during growth on methane and methanol

Background: Methanotrophs play an important role in biotechnological applications, with their ability to utilize single carbon (C1) feedstock such as methane and methanol to produce a range of high-value compounds. A newly isolated obligate methanotroph strain, Methylomonas sp. DH-1, became a platform strain for biotechnological applications because it has proven capable of producing chemicals, fuels, and secondary metabolites from methane and methanol. In this study, transcriptome analysis with RNA-seq was used to investigate the transcriptional change of Methylomonas sp. DH-1 on methane and methanol. This was done to improve knowledge about C1 assimilation and secondary metabolite pathways in this promising, but under-characterized, methane-bioconversion strain. Results: We integrated genomic and transcriptomic analysis of the newly isolated Methylomonas sp. DH-1 grown on methane and methanol. Detailed transcriptomic analysis indicated that (i) Methylomonas sp. DH-1 possesses the ribulose monophosphate (RuMP) cycle and the Embden-Meyerhof-Parnas (EMP) pathway, which can serve as main pathways for C1 assimilation, (ii) the existence and the expression of a complete serine cycle and a complete tricarboxylic acid (TCA) cycle might contribute to methane conversion and energy production, and (iii) the highly active endogenous plasmid pDH1 may code for essential metabolic processes. Comparative transcriptomic analysis on methane and methanol as a sole carbon source revealed different transcriptional responses of Methylomonas sp. DH-1, especially in C1 assimilation, secondary metabolite pathways, and oxidative stress. Especially, these results suggest a shift of central metabolism when substrate changed from methane to methanol in which formaldehyde oxidation pathway and serine cycle carried more flux to produce acetyl-coA and NADH. Meanwhile, downregulation of TCA cycle when grown on methanol may suggest a shift of its main function is to provide de novo biosynthesis, but not produce NADH. Conclusions: This study provides insights into the transcriptomic profile of Methylomonas sp. DH-1 grown on major carbon sources for C1 assimilation, providing in-depth knowledge on the metabolic pathways of this strain. These observations and analyses can contribute to future metabolic engineering with the newly isolated, yet under-characterized, Methylomonas sp. DH-1 to enhance its biochemical application in relevant industries