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Today's complex software systems are neither secure nor reliable. The rudimentary software protection primitives provided by current hardware forces systems to run many distrusting software components (e.g., procedures, libraries, plugins, modules) in the same protection domain, or otherwise suffer degraded performance from address space switches. We present CODOMs (COde-centric memory DOMains), a novel architecture that can provide finer-grained isolation between software components with effectively zero run-time overhead, all at a fraction of the complexity of other approaches. An implementation of CODOMs in a cycle-accurate full-system x86 simulator demonstrates that with the right hardware support, finer-grained protection and run-time performance can peacefully coexist.We would like to thank Lluc Alvarez, Javier Cabezas, Ana Jokanovic, Marc Jorda, Carlos Villavieja, our shepherd Mohit Tiwari and the anonymous reviewers for their help and comments on this paper. This work has received funding from: the European Commission through TERAFLUX (FP7-249013) and RoMoL (GA-321253); the Spanish Government through Programa Severo Ochoa (SEV-2011-0067); the Spanish Min­istry of Science and Technology through TIN2007-60625 and TIN2012-34557; the Israel Science Foundation (grant 769/12 and equipment grant 1719112); and the Ministry of Science and Technology, Israel. Yoav Etsion was supported by the Center for Computer Engineering at the Technion.Peer ReviewedPostprint (published version

Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo

Abstract—Memory overcommitment enables cloud providers to host more virtual machines on a single physical server, exploiting spare CPU and I/O capacity when physical memory becomes the bottleneck for virtual machine deployment. However, overcommiting memory can also cause noticeable application performance degradation. We present Ginkgo, a policy frame-work for overcomitting memory in an informed and automated fashion. By directly correlating application-level performance to memory, Ginkgo automates the redistribution of scarce memory across all virtual machines, satisfying performance and capacity constraints. Ginkgo also achieves memory gains for traditionally fixed-size Java applications by coordinating the redistribution of available memory with the activities of the Java Virtual Machine heap. When compared to a non-overcommited system, Ginkgo runs the DayTrader 2.0 and SPECWeb 2009 benchmarks with the same number of virtual machines while saving up to 73% (50 % omitting free space) of a physical server’s memory while keeping application performance degradation within 7%. I

Using SMT to accelerate nested virtualization

IaaS datacenters offer virtual machines (VMs) to their clients, who in turn sometimes deploy their own virtualized environments, thereby running a VM inside a VM. This is known as nested virtualization. VMs are intrinsically slower than bare-metal execution, as they often trap into their hypervisor to perform tasks like operating virtual I/O devices. Each VM trap requires loading and storing dozens of registers to switch between the VM and hypervisor contexts, thereby incurring costly runtime overheads. Nested virtualization further magnifies these overheads, as every VM trap in a traditional virtualized environment triggers at least twice as many traps. We propose to leverage the replicated thread execution resources in simultaneous multithreaded (SMT) cores to alleviate the overheads of VM traps in nested virtualization. Our proposed architecture introduces a simple mechanism to colocate different VMs and hypervisors on separate hardware threads of a core, and replaces the costly context switches of VM traps with simple thread stall and resume events. More concretely, as each thread in an SMT core has its own register set, trapping between VMs and hypervisors does not involve costly context switches, but simply requires the core to fetch instructions from a different hardware thread. Furthermore, our inter-thread communication mechanism allows a hypervisor to directly access and manipulate the registers of its subordinate VMs, given that they both share the same in-core physical register file. A model of our architecture shows up to 2.3× and 2.6× better I/O latency and bandwidth, respectively. We also show a software-only prototype of the system using existing SMT architectures, with up to 1.3× and 1.5× better I/O latency and bandwidth, respectively, and 1.2--2.2× speedups on various real-world applications

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world’s highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%.Peer ReviewedPostprint (published version

Out-of-Band Detection of Boot-Sequence Termination Events

The popularization of both virtualization and CDP technologies mean that we can now watch disk accesses of systems from entities which are not controlled by the OS. This is a rich source of information about the system’s inner workings. In this paper, we explore one way of mining the stream of data, to determine if the system had finished booting. Systems which we detect as failing to boot (or taking too long to boot) are flagged for further manual or automatic remediation. By performing this detection out-of-band, we gain a head start on any detection scheme that runs within the OS, and therefore must wait for the boot event to finish. Additionally, our scheme is agnostic to file-system layout and to kernel architecture. We implemented our solution for the x86 architecture under two different virtualization platforms, and tested it on both Windows and Linux virtual machines. Under a variety of workloads and configurations, our detector managed to successfully identify the boot termination event, in most cases within 5 seconds of the event