Miracle-dz/UniFAR-FTUs huggingface dataset:
Alleviating Garbage Collection Interference Through Spatial Separation in All Flash Arrays

We present SWAN, a novel All Flash Array (AFA) management scheme. Recent ﬂash SSDs provide high I/O bandwidth (e.g., 3-10GB/s) so the storage bandwidth can easily surpass the network bandwidth by aggregating a few SSDs. However, it is still challenging to unlock the full performance of SSDs. The main source of performance degradation is garbage collection (GC). We ﬁnd that existing AFA designs are susceptible to GC at SSD-level and AFA software-level. In designing SWAN, we aim to alleviate the performance interference caused by GC at both levels. Unlike the commonly-used temporal separation approach that performs GC at idle time, we take a spatial separation approach that partitions SSDs into the front-end SSDs dedicated to serve write requests and the back-end SSDs where GC is performed. Compared to temporal separation of GC and application I/O, which is hard to be controlled by AFA software, our approach guarantees that the storage bandwidth always matches the full network performance without being inter-fered by AFA-level GC. Our analytical model conﬁrms this if the size of front-end SSDs and the back-end SSDs are properly conﬁgured. We provide extensive evaluations that show SWAN is effective for a variety of workloads.
Asynchronous I/O Stack: A Low-latency Kernel I/O Stack for Ultra-Low Latency SSDs

Today’s ultra-low latency SSDs can deliver an I/O latency of sub-ten microseconds. With this dramatically shrunken device time, operations inside the kernel I/O stack, which were traditionally considered lightweight, are no longer a negligible portion. This motivates us to reexamine the storage I/O stack design and propose an asynchronous I/O stack (AIOS), where synchronous operations in the I/O path are replaced by asynchronous ones to overlap I/O-related CPU operations with device I/O. The asynchronous I/O stack leverages a lightweight block layer specialized for NVMe SSDs using the page cache without block I/O scheduling and merging, thereby reducing the sojourn time in the block layer. We prototype the proposed asynchronous I/O stack on the Linux kernel and evaluate it with various workloads. Synthetic FIO benchmarks demonstrate that the application-perceived I/O latency falls into single-digit microseconds for 4 KB random reads on Optane SSD, and the overall I/O latency is reduced by 15–33% across varying block sizes. This I/O latency reduction leads to a significant performance improvement of real-world applications as well: 11–44% IOPS increase on RocksDB and 15–30% throughput improvement on Filebench and OLTP workloads.
A pipelined temporal difference imager

A 189/spl times/182 Active Pixel Sensor (APS) for temporal difference computation is presented. The temporal difference imager (TDI), fabricated in AMI 0.5 /spl mu/ process, contains in-pixel storage elements for previous and current frames. A correlated double sampling circuit is used to suppress the fixed pattern noise on both images and direct difference on the corrected images is also computed. The pixel area occupies 25 /spl mu/ by 25 /spl mu/, with fill factor of 30%. An efficient pipeline architecture for difference readout is implemented, allowing 8 bit precision of the difference imager and low temporal drop between the stored and current images. The chip consumes 30 mW at 50 fps from 5 V power supply.
Centerline-based vessel segmentation using graph cuts

Complete and accurate segmentation of the vessel from 3D (three dimensional) CT images is challenging due to lowcontrast, combined with noise, and high variation of vessel size. We describe a novel centerline-based method to produce the accurate vessel segmentation. It starts with locating vessel centerline which will be used as guidance, followed by graph cuts, with edge-weights depending on the intensity of the centerline. The main advantage of our framework is that it detects vessel boundary in problematic regions that contain small vessels and noise. A comparison has been made with two state-of-the-art vessel segmentation methods. Quantitative results on synthetic data indicate that our method is more accurate than these methods. Furthermore, experimental results on clinical data have shown that our method is capable of detecting more detailed information of vessel. It is more accurate and robust that these state-of-the-art methods and is, therefore, more suited for automatic vessel extraction.
On the costs and benefits of using partial-order methods for the verification of concurrent systems

Veri(cid:12)cation by state-space exploration is one of the most successful strategies for analyzing the correctness of (cid:12)nite-state concurrent reactive systems. Partial-order methods are algorithms for dynamically pruning the state space of such systems without incurring the risk of any incompleteness in the veri(cid:12)cation results. This paper presents results of experiments performed with these algorithms on real protocol examples, and discusses the practical signi(cid:12)cance of partial-order methods.
SmartDedup: Optimizing Deduplication for Resource-constrained Devices

Storage on smart devices such as smartphones and the Internet of Things has limited performance, capacity, and endurance. Deduplication has the potential to address these limitations by eliminating redundant I/Os and data, but it must be considered under the various resource constraints of the devices. This paper presents SmartDedup, a deduplication solution optimized for resourceconstrained devices. It proposes a novel architecture that supports symbiotic in-line and out-of-line deduplication to take advantage of their complementary strengths and allow them to be adapted according to a device’s current resource availability. It also cohesively combines in-memory and on-disk fingerprint stores to minimize the memory overhead while achieving a good level of deduplication. SmartDedup is prototyped on EXT4 and F2FS and evaluated using benchmarks, workloads generated from real-world device images, and traces collected from real-world devices. The results show that SmartDedup substantially improves I/O performance (e.g., increases write and read throughput by 31.1% and 32%, respectively for an FIO experiment with 25% duplication ratio), reduces flash writes (e.g., by 70.9% in a trace replay experiment with 75.8% duplication ratio), and saves space usage (e.g., by 45% in a DEDISbench experiment with 46.1% duplication ratio) with low memory, storage, and battery overhead, compared to both native file systems and related deduplication solutions.
Knowledge-based object recognition and model generation

We will present a new system for knowledge-based image analysis which exploits the benefits of object oriented programming. The knowledge base is built using a formal language for semantic nets, which are already successfully applied in an industrial project. The knowledge base is compiled into an image analysis program. Time consuming search in the knowledge base can thus be avoided. The system provides a general interface to pattern analysis techniques which are included in the generated program as specified by the user. The approach combines the advantages of a compiled program for a special purpose with the flexibility of a general knowledge base tool. The resulting program is used for the reconstruction of the 3D shape of industrial objects using stereo techniques. Images are taken from several viewpoints. Models of 3D objects are then created by an integration of the segmentation data.
E3: Energy-Efficient Microservices on SmartNIC-Accelerated Servers

We investigate the use of SmartNIC-accelerated servers to execute microservice-based applications in the data center. By offloading suitable microservices to the SmartNIC’s lowpower processor, we can improve server energy-efficiency without latency loss. However, as a heterogeneous computing substrate in the data path of the host, SmartNICs bring several challenges to a microservice platform: network traffic routing and load balancing, microservice placement on heterogeneous hardware, and contention on shared SmartNIC resources. We present E3, a microservice execution platform for SmartNIC-accelerated servers. E3 follows the design philosophies of the Azure Service Fabric microservice platform and extends key system components to a SmartNIC to address the above-mentioned challenges. E3 employs three key techniques: ECMP-based load balancing via SmartNICs to the host, network topology-aware microservice placement, and a data-plane orchestrator that can detect SmartNIC overload. Our E3 prototype using Cavium LiquidIO SmartNICs shows that SmartNIC offload can improve cluster energy-efficiency up to 3× and cost efficiency up to 1.9× at up to 4% latency cost for common microservices, including real-time analytics, an IoT hub, and virtual network functions.
Filesystem Aging: It's more Usage than Fullness

Filesystem fragmentation is a first-order performance problem that has been the target of many heuristic and algorithmic approaches. Real-world application benchmarks show that common filesystem operations cause many filesystems to fragment over time, a phenomenon known as filesystem aging. This paper examines the common assumption that space pressure will exacerbate fragmentation. Our microbenchmarks show that space pressure can cause a substantial amount of inter-file and intra-file fragmentation. However, on a “real-world” application benchmark, space pressure causes fragmentation that slows subsequent reads by only 20% on ext4, relative to the amount of fragmentation that would occur on a file system with abundant space. The other file systems show negligible additional degradation under space pressure. Our results suggest that the effect of free-space fragmentation on read performance is best described as accelerating the filesystem aging process. The effect on write performance is non-existent in some cases, and, in most cases, an order of magnitude smaller than the read degradation from fragmentation cause by normal usage.
SemperOS: A Distributed Capability System

Capabilities provide an efﬁcient and secure mechanism for ﬁne-grained resource management and protection. However, as the modern hardware architectures continue to evolve with large numbers of non-coherent and heterogeneous cores, we focus on the following research question: can capability systems scale to modern hardware architectures? In this work, we present a scalable capability system to drive future systems with many non-coherent heterogeneous cores. More speciﬁcally, we have designed a distributed capability system based on a HW/SW co-designed capability system. We analyzed the pitfalls of distributed capability operations running concurrently and built the protocols in accordance with the insights. We have incorporated these distributed capability management protocols in a new microkernel-based OS called S EMPER OS. Our OS operates the system by means of multiple microkernels, which employ distributed capabilities to provide an efﬁcient and secure mechanism for ﬁne-grained access to system resources. In the evaluation we investigated the scalability of our algorithms and run applications (Nginx, LevelDB, SQLite, PostMark, etc.), which are heavily dependent on the OS services of S EMPER OS. The results indicate that there is no inherent scalability limitation for capability systems. Our evaluation shows that we achieve a parallel efﬁciency of 70% to 78% when examining a system with 576 cores executing 512 application instances while using 11% of the system’s cores for OS services.
LXDs: Towards Isolation of Kernel Subsystems

Modern operating systems are monolithic. Today, however, lack of isolation is one of the main factors undermining security of the kernel. Inherent complexity of the kernel code and rapid development pace combined with the use of unsafe, low-level programming language results in a steady stream of errors. Even after decades of efforts to make commodity kernels more secure, i.e., development of numerous static and dynamic approaches aimed to prevent exploitation of most common errors, several hundreds of serious kernel vulnerabilities are reported every year. Unfortunately, in a monolithic kernel a single exploitable vulnerability potentially provides an attacker with access to the entire kernel. Modern kernels need isolation as a practical means of confining the effects of exploits to individual kernel subsystems. Historically, introducing isolation in the kernel is hard. First, commodity hardware interfaces provide no support for efficient, fine-grained isolation. Second, the complexity of a modern kernel prevents a naive decomposition effort. Our work on Lightweight Execution Domains (LXDs) takes a step towards enabling isolation in a full-featured operating system kernel. LXDs allow one to take an existing kernel subsystem and run it inside an isolated domain with minimal or no modifications and with a minimal overhead. We evaluate our approach by developing isolated versions of several performance-critical device drivers in the Linux kernel.
A theoretical model for the Virtual Personal Assistant

The theoretical model for a Virtual Personal Assistant (VPA) is part of a larger research program to develop a new model for a Decision Support System (DSS) that learns from interactions with an individual to build a personalized relationship [1]. We have hypothesized within this research program that end user supporting technologies that develop a personal relationship with will provide unique benefits to the user by providing a way to contextually explore a problem space with the user [2]. The purpose of this poster is to visualize how the proposed VPA would interact with other services, and to highlight who is in control of the end users personal data. The VPA will utilize natural language processing, learning capabilities and response variance such as simulated emotions to explore a problem space with a professional individual. Natural language processing and learning capabilities have been used in a number of modern technologies to provide more refined and useful outputs to the end user. Examples of this can be found in systems such as ​Apple’s Siri [3], ​Microsoft’s Cortana [4], ​Amazon’s Alexa [5] and ​Google Assistant [6]. The difference with these technologies is that they categories the end user based upon the information they gather and give suggestions based upon other users within this category. While there are benefits to this approach in a casual context, a system such as the VPA that learns entirely from a professional individual is able to form its own perspective which is an imitation of the perspective of the unique user. With this perspective the system is able to analyze and explore uncertain or ambiguous problem spaces and still provide a relevant and useful discussion with the end user. The inclusion of response variance steps the VPA away from technologies such as ​IBM’s Watson ​[7], where the response to an input is always what the system deems as the most “correct” output. The issue with question-answering systems such as this is it doesn’t account for uncertain or ambiguous situations where there may be many equally valid correct answers, or there may be none. The poster associated with this abstract has been produced as a first step in visualizing the differences between the proposed VPA style of DSS in comparison to other intelligent agents such as Siri and Alexa. Where previous posters have focused on the internal process of a VPA’s functionality [8], this poster looks at how the VPA stores data and interacts with external entities using a graph theory approach. To that end, we have produced two models: one for a Virtual Personal Assistant, and one for other intelligent agents. Proceedings of STPIS'19
A private key cryptosystem based upon enforced random substitution scheme

Proposes a private key cryptosystem in which a specially designed permutation table is used as an enciphering/deciphering key. By the permutation table, an enforced random substitution scheme substitutes the characters in a plaintext message. It is hard to guess the correct plaintext characters from known ciphertext characters. The secure measurement and some possible attacks on the proposed cryptosystem are also discussed. <<ETX>>
An efficient CMOS buffer for driving large capacitive loads

A CMOS class AB high-drive buffer suitable for driving large capacitive and moderate resistive loads is presented. The buffer, designed using 3-/spl mu/m technology, occupies only 100 mils/SUP 2/ of area and dissipates 1.5 mW of DC power from a /spl plusmn/2.5-V supply, yet it is capable of driving a 5000-pF capacitor at over 100-kHz clocking frequency. The buffer achieves good slew rate and fast settling by entering into a high-drive state during slewing and returning to a low-power wide-band state during the settling period. Unconditional stability is attained when C/SUB L//spl ges/100 pF and R/SUB L//spl ges/10 k/spl Omega/. Total harmonic distortion is below 0.5% for over 70% of the full supply range.
Community Memory Activation with Collaboration Patterns

We present a model of collaboration patterns as reu sable conceptual structures capturing essential col laboration requirements. These patterns include goal patterns (what is the collaboration about? ), communication patterns (how does communication to accomplish goals take place? ), information patterns (what content knowledge is essential to satisfy co llaborative and communicative goals? ), task patterns (what particular information patterns are needed f or particular action or interaction goals? ), and meta-patterns (what patterns are necessary to interpret, link an d assess the quality of the other collaboration patterns? ). We show how these patterns can be used to activate communities of practice by improving th eir collective, distributed memory of communicative interactions and information. We outline an approach that structur es how collaboration patterns in communities of practice can be elicited , represented, analyzed, and applied. By presenting a realistic scenario, we illustrate how community memory could be activated in practice.
Magnetic Resonance Imaging in Pediatric Migraine

ABSTRACT: This literature review provides an overview of the research using magnetic resonance imaging (MRI) in pediatric migraine and compares findings with the adult migraine literature. A literature search using PubMed was conducted using all relevant sources up to February 2019. Using MRI methods to categorize and explain pediatric migraine in comparison with adult migraine is important, in order to recognize and appreciate the differences between the two entities, both clinically and physiologically. We aim to demonstrate the differences and similarities between pediatric and adult migraine using data from white matter and gray matter structural studies, cerebral perfusion, metabolites, and functional MRI (fMRI) studies, including task-based and resting-state blood oxygen level-dependent studies. By doing this we identify areas that need further research, as well as possible areas where intervention could alter outcomes. RÉSUMÉ: Utiliser des examens d’IRM dans le cas de jeunes patients souffrant de migraine. Cette revue de littérature entend fournir un survol des travaux de recherche explorant l’utilisation d’examens d’IRM dans le cas de jeunes patients souffrant de migraine. Elle vise aussi à comparer nos observations à celles que l’on trouve dans la littérature portant sur les cas de migraine chez les adultes. Au moyen de PubMed, nous avons effectué une recherche bibliographique pour ensuite utiliser toutes les références jugées pertinentes et publiées avant février 2019. Le fait d’utiliser des méthodes d’imagerie afin de catégoriser et d’expliquer les cas de migraine chez les enfants, et ce, en comparaison avec les cas de migraine chez l’adulte, est important afin de pouvoir reconnaître et d’identifier les différences tant sur le plan clinique que physiologique. Notre intention est ici de faire ressortir ces différences (mais aussi des similitudes) au moyen de données obtenues dans le cadre d’études structurales de la matière blanche et de la matière grise et d’études portant sur la perfusion cérébrale, les métabolites et les IRM fonctionnelles, ce qui inclut le signal BOLD (blood oxygen level dependent) à l’état de repos ou lors de l’exécution de tâches. En procédant à cette étude, nous voulons identifier les domaines qui devraient être explorés davantage de même que les domaines où des interventions pourraient modifier l’évolution de l’état de santé des patients.
Ling adders in CMOS standard cell technologies

Two level carry look-ahead (CLA) and novel parallel-prefix Ling adder architectures are introduced in this paper. The adders resulting from these architectures, as well as from the well known single level CLA Ling adder architecture, are compared against traditional adders using CMOS realizations. The results reveal that Ling architectures are more attractive in several cases.
Whole-exome and RNA sequencing reveals novel insights into the pathogenesis of HPV associated cervical cancer.

BACKGROUND Worldwide, cervical cancer is the fouth leading cause of deaths in gynecological oncology. Although the causes of cervical cancer have been extensively investigated, understanding of its exact pathogenesis remains incomplete. OBJECTIVE This study aimed to identify alterations of genome and transcriptome of HPV associated cervical cancer pathogenesis using multi-omics approaches. METHODS Cervical cancer and matched adjacent non-tumor specimens of one HPV16+ and two HPV- patients were sampled for whole-exome sequencing (WES) and RNA sequencing to characterize DNA mutations and gene expression profiles. WES and Affymetrix SNP 6.0 arrays data were analyzed from 6 HPV- and 93 HPV16+ cervical cancer patients in the cancer genome atlas (TCGA) database, as an independent validation group. RESULTS WES identified 64 somatic mutation genes in tumors of 3 patients. HPV16+ tumors got fewer somatic mutated genes than HPV- tumors, which was validated by TCGA results. In this study, somatic mutated profile, CNV and gene expression heat map presented that HPV16+ tumors was distinct with HPV- tumors. The most significant altered pathways and GO terms were both related with cell cycle. Integrated analysis of multi-omics showed positive correlation between gene expression level and copy numbers. CONCLUSIONS The results of this study provided novel insights into the pathogenesis of HPV associated cervical cancer.
Molecular Genotyping of Hepatitis A Virus, California, USA, 2017–2018

We implemented subgenomic and whole-genome sequencing to support the investigation of a large hepatitis A virus outbreak among persons experiencing homelessness, users of illicit drugs, or both in California, USA, during 2017–2018. Genotyping data helped confirm case-patients, track chains of transmission, and monitor the effectiveness of public health control measures.
Quantum-Induced Symmetry Breaking in the Deuterated Dihydroanthracenyl Radical.

The hydrogen-atom adduct with anthracene, 9-dihydroanthracenyl radical (C14H11), and its deuterated analogue, have been identified by laser spectroscopy coupled to time-of-flight mass spectrometry, supported by time-dependent density functional theory calculations. The electronic spectrum of 9-dihydroanthracenyl radical exhibits an origin band at 19115 cm-1 and its ionization energy was determined to be 6.346(1) eV. The spectra reveal a low-frequency vibrational progression corresponding to a mode described by a butterfly-inversion. In the deuterated analogue, a zero-point-energy imbalance along this coordinate is found to lead to a doubling of the observed spectral lines in the progression. This is attributed to quantum-induced symmetry breaking as previously observed in isotopologues of CH5+.