An Analysis of Performance Interference Effects on Energy-Efficiency of Virtualized Cloud Environments

Co-allocated workloads in a virtualized computing environment often have to compete for resources, thereby suffering from performance interference. While this phenomenon has a direct impact on the Quality of Service provided to customers, it also changes the patterns of resource utilization and reduces the amount of work per Watt consumed. Unfortunately, there has been only limited research into how performance interference affects energy-efficiency of servers in such environments. In reality, there is a highly dynamic and complicated correlation among resource utilization, performance interference and energy-efficiency. This paper presents a comprehensive analysis that quantifies the negative impact of performance interference on the energy-efficiency of virtualized servers. Our analysis methodology takes into account the heterogeneous workload characteristics identified from a real Cloud environment. In particular, we investigate the impact due to different workload type combinations and develop a method for approximating the levels of performance interference and energy-efficiency degradation. The proposed method is based on profiles of pair combinations of existing workload types and the patterns derived from the analysis. Our experimental results reveal a non-linear relationship between the increase in interference and the reduction in energy-efficiency as well as an average precision within +/-5% of error margin for the estimation of both parameters. These findings provide vital information for research into dynamic trade-offs between resource utilization, performance, and energy-efficiency of a data center

Fission yeast 26S proteasome mutants are multi-drug resistant due to stabilization of the pap1 transcription factor

Here we report the result of a genetic screen for mutants resistant to the microtubule poison methyl benzimidazol-2-yl carbamate (MBC) that were also temperature sensitive for growth. In total the isolated mutants were distributed in ten complementation groups. Cloning experiments revealed that most of the mutants were in essential genes encoding various 26S proteasome subunits. We found that the proteasome mutants are multi-drug resistant due to stabilization of the stress-activated transcription factor Pap1. We show that the ubiquitylation and ultimately the degradation of Pap1 depend on the Rhp6/Ubc2 E2 ubiquitin conjugating enzyme and the Ubr1 E3 ubiquitin-protein ligase. Accordingly, mutants lacking Rhp6 or Ubr1 display drug-resistant phenotypes

A dose-finding Phase 2 study of single agent isatuximab (anti-CD38 mAb) in relapsed/refractory multiple myeloma

A Phase 2 dose-finding study evaluated isatuximab, an anti-CD38 monoclonal antibody, in relapsed/refractory multiple myeloma (RRMM; NCT01084252). Patients with ?3 prior lines or refractory to both immunomodulatory drugs and proteasome inhibitors (dual refractory) were randomized to isatuximab 3 mg/kg every 2 weeks (Q2W), 10 mg/kg Q2W(2 cycles)/Q4W, or 10 mg/kg Q2W. A fourth arm evaluated 20 mg/kg QW(1 cycle)/Q2W. Patients (N = 97) had a median (range) age of 62 years (38-85), 5 (2-14) prior therapy lines, and 85% were double refractory. The overall response rate (ORR) was 4.3, 20.0, 29.2, and 24.0% with isatuximab 3 mg/kg Q2W, 10 mg/kg Q2W/Q4W, 10 mg/kg Q2W, and 20 mg/kg QW/Q2W, respectively. At doses ?10 mg/kg, median progression-free survival and overall survival were 4.6 and 18.7 months, respectively, and the ORR was 40.9% (9/22) in patients with high-risk cytogenetics. CD38 receptor density was similar in responders and non-responders. The most common non-hematologic adverse events (typically grade ?2) were nausea (34.0%), fatigue (32.0%), and upper respiratory tract infections (28.9%). Infusion reactions (typically with first infusion and grade ?2) occurred in 51.5% of patients. In conclusion, isatuximab is active and generally well tolerated in heavily pretreated RRMM, with greatest efficacy at doses ?10 mg/kg

Regional microbial signatures positively correlate with differential wine phenotypes: evidence for a microbial aspect to terroir

Many crops display differential geographic phenotypes and sensorial signatures, encapsulated by the concept of terroir. The drivers behind these differences remain elusive, and the potential contribution of microbes has been ignored until recently. Significant genetic differentiation between microbial communities and populations from different geographic locations has been demonstrated, but crucially it has not been shown whether this correlates with differential agricultural phenotypes or not. Using wine as a model system, we utilize the regionally genetically differentiated population of Saccharomyces cerevisiae in New Zealand and objectively demonstrate that these populations differentially affect wine phenotype, which is driven by a complex mix of chemicals. These findings reveal the importance of microbial populations for the regional identity of wine, and potentially extend to other important agricultural commodities. Moreover, this suggests that long-term implementation of methods maintaining differential biodiversity may have tangible economic imperatives as well as being desirable in terms of employing agricultural practices that increase responsible environmental stewardship

Development and characterization of a microfluidic model of the tumour microenvironment

The physical microenvironment of tumours is characterized by heterotypic cell interactions and physiological gradients of nutrients, waste products and oxygen. This tumour microenvironment has a major impact on the biology of cancer cells and their response to chemotherapeutic agents. Despite this, most in vitro cancer research still relies primarily on cells grown in 2D and in isolation in nutrient- and oxygen-rich conditions. Here, a microfluidic device is presented that is easy to use and enables modelling and study of the tumour microenvironment in real-time. The versatility of this microfluidic platform allows for different aspects of the microenvironment to be monitored and dissected. This is exemplified here by real-time profiling of oxygen and glucose concentrations inside the device as well as effects on cell proliferation and growth, ROS generation and apoptosis. Heterotypic cell interactions were also studied. The device provides a live ‘window’ into the microenvironment and could be used to study cancer cells for which it is difficult to generate tumour spheroids. Another major application of the device is the study of effects of the microenvironment on cellular drug responses. Some data is presented for this indicating the device’s potential to enable more physiological in vitro drug screening

Search for Gravitational Waves from Primordial Black Hole Binary Coalescences in the Galactic Halo

We use data from the second science run of the LIGO gravitational-wave detectors to search for the gravitational waves from primordial black hole (PBH) binary coalescence with component masses in the range 0.2--$1.0 M_\odot$. The analysis requires a signal to be found in the data from both LIGO observatories, according to a set of coincidence criteria. No inspiral signals were found. Assuming a spherical halo with core radius 5 kpc extending to 50 kpc containing non-spinning black holes with masses in the range 0.2--$1.0 M_\odot$, we place an observational upper limit on the rate of PBH coalescence of 63 per year per Milky Way halo (MWH) with 90% confidence.Comment: 7 pages, 4 figures, to be submitted to Phys. Rev.

Array algorithms for H^2 and H^∞ estimation

Currently, the preferred method for implementing H^2 estimation algorithms is what is called the array form, and includes two main families: square-root array algorithms, that are typically more stable than conventional ones, and fast array algorithms, which, when the system is time-invariant, typically offer an order of magnitude reduction in the computational effort. Using our recent observation that H^∞ filtering coincides with Kalman filtering in Krein space, in this chapter we develop array algorithms for H^∞ filtering. These can be regarded as natural generalizations of their H^2 counterparts, and involve propagating the indefinite square roots of the quantities of interest. The H^∞ square-root and fast array algorithms both have the interesting feature that one does not need to explicitly check for the positivity conditions required for the existence of H^∞ filters. These conditions are built into the algorithms themselves so that an H^∞ estimator of the desired level exists if, and only if, the algorithms can be executed. However, since H^∞ square-root algorithms predominantly use J-unitary transformations, rather than the unitary transformations required in the H^2 case, further investigation is needed to determine the numerical behavior of such algorithms