Classification-driven search for effective sm partitioning in multitasking GPUs

Graphics processing units (GPUs) feature an increasing number of streaming multiprocessors (SMs) with each successive generation. At the same time, GPUs are increasingly widely adopted in cloud services and data centers to accelerate general-purpose workloads. Running multiple applications on a GPU in such environments requires effective multitasking support. Spatial multitasking in which independent applications co-execute on different sets of SMs is a promising solution to share GPU resources. Unfortunately, how to effectively partition SMs is an open problem. In this paper, we observe that compared to widely-used even partitioning, dynamic SM partitioning based on the characteristics of the co-executing applications can significantly improve performance and power efficiency. Unfortunately, finding an effective SM partition is challenging because the number of possible combinations increases exponentially with the number of SMs and co-executing applications. Through offline analysis, we find that first classifying workloads, and then searching an effective SM partition based on the workload characteristics can significantly reduce the search space, making dynamic SM partitioning tractable. Based on these insights, we propose Classification-Driven search (CD-search) for low-overhead dynamic SM partitioning in multitasking GPUs. CD-search first classifies workloads using a novel off-SM bandwidth model, after which it enters the performance mode or power mode depending on the workload's characteristics. Both modes follow a specific search strategy to quickly determine the optimum SM partition. Our evaluation shows that CD-search improves system throughput by 10.4% on average (and up to 62.9%) over even partitioning for workloads that are classified for the performance mode. For workloads classified for the power mode, CD-search reduces power consumption by 25% on average (and up to 41.2%). CD-search incurs limited runtime overhead

Planar Optical Nanoantennas Resolve Cholesterol-Dependent Nanoscale Heterogeneities in the Plasma Membrane of Living Cells

Optical nanoantennas can efficiently confine light into nanoscopic hotspots, enabling single-molecule detection sensitivity at biological relevant conditions. This innovative approach to breach the diffraction limit offers a versatile platform to investigate the dynamics of individual biomolecules in living cell membranes and their partitioning into cholesterol-dependent lipid nanodomains. Here, we present optical nanoantenna arrays with accessible surface hotspots to study the characteristic diffusion dynamics of phosphoethanolamine (PE) and sphingomyelin (SM) in the plasma membrane of living cells at the nanoscale. Fluorescence burst analysis and fluorescence correlation spectroscopy performed on nanoantennas of different gap sizes show that, unlike PE, SM is transiently trapped in cholesterol-enriched nanodomains of 10 nm diameter with short characteristic times around 100 μs. The removal of cholesterol led to the free diffusion of SM, consistent with the dispersion of nanodomains. Our results are consistent with the existence of highly transient and fluctuating nanoscale assemblies enriched by cholesterol and sphingolipids in living cell membranes, also known as lipid rafts. Quantitative data on sphingolipids partitioning into lipid rafts is crucial to understand the spatiotemporal heterogeneous organization of transient molecular complexes on the membrane of living cells at the nanoscale. The proposed technique is fully biocompatible and thus provides various opportunities for biophysics and live cell research to reveal details that remain hidden in confocal diffraction-limited measurements.Peer ReviewedPostprint (author's final draft

Set Partitioning to Construct Block Coded Modulation with the Presence of Spatial Modulation in MIMO Systems

In this paper, enhancing the BER performance of multiple-input multiple-output systems (MIMO) is considered by using Block Coded Spatial Modulation (BCSM). It is a combination of Block Coded Modulation (BCM) used set partitioning to formulate the code, and the spatial Modulation (SM) as a transmission technique of MIMO systems. To achieve this, the idea of MIMO communication systems, block coded modulation, set partitioning, multi stage decoding and spatial modulation have been combined. Matrix Laboratory (MATLAB) is used for the simulation and Bit Error Rate (BER) is obtained and verified. The simulation results for the combination of BCM with SM show that there is a significant improvement in BER performance compared to the classical SM techniques. It gives an approximately 5 dB enhancing of BER performance from the use of SM only, and about 3 dB enhancing from the use of coded information bits with SM

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multi-level fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns

TIR-Raman Spectroscopy of Model Supported Lipid Bilayers

In this thesis the technique of total internal reflection (TIR) Raman spectroscopy was applied to study the properties and interactions of supported lipid bilayers (SLBs) at the silica-water interface, both kinetically and at equilibrium. First, the formation kinetics of SLB systems from lipid aggregate suspensions was investigated. The lipid systems comprised POPC, POPE, egg-SM and a 1:1:1 mixture of POPE, egg-SM and cholesterol, all in tris buffer with and without added NaCl and CaCl2. Vesicle/aggregate suspensions were prepared by bath sonication and their size distributions were quantified with nanoparticle tracking analysis (NTA). The additional group I and group II salts altered the size distribution of the lipid vesicle/aggregate suspensions produced and played large role in the kinetics observed. For POPC, by changing the buffer conditions the adsorption of extraneous vesicles on the SLB could be tuned. For POPE, a previously unknown formation pathway was observed, whereby larger aggregates spread following adsorption to the interface. For the mixed system, the final ratio of components was found to be the same as that in the initial suspension. Second, the physical transformations of SLBs composed of DMPC, egg-SM and POPE were examined and the role of NaCl and CaCl2 upon these phase transitions was investigated. Raman spectra were obtained as a function of temperature and quantified using order parameter analysis. The resulting data were interpreted using the Zimm and Bragg model, which yielded the cooperativity of each phase transition. Cooperativity was controlled by the interfacial energy between regions of Lβ/Pβ and Lα phase. The presence or absence of the above salts altered the number of molecules within the cooperative unit for each of the species listed and controlled the interfacial energy. The most striking result was that of the POPE main phase transition with added CaCl2, for which cooperativity was massively reduced yielding a structural transition over a broad temper- ature range; AFM images confirmed the nature of this transition, showing domain like structures over a matching broad temperature range. Third, the interaction of SDS with SLBs composed of POPE, POPC, egg-SM and the 1:1:1 mixture of POPE, egg-SM and cholesterol was explored. Partitioning isotherms were constructed from equilibrium data and interpreted with a non-ideal partitioning model previously applied to vesicular systems. Accounting for the theoretical build-up of surface charge was found to be unnecessary probably owing to counterion binding. Kinetic data of the partitioning process for the different SLBs were obtained and qualitatively interpreted. For POPC at low dSDS concentrations dSDS translocation or flip-flop from the distal to proximal bilayer leaflets did not occur. At higher concentrations a period of rapid uptake lasting for approximately 100 s was followed by a slower increase lasting on the order of 10 minutes thus indicating that translocation was occurring. Upon subsequent rinsing, there was an initial rapid decrease in dSDS followed by a slower protracted decrease indicating that reverse flip-flop was occurring. The most intriguing result was that of the overall lipid signal upon rinsing, often it was observed to recover to levels equal to those prior to dSDS addition. These data suggest the formation of blebs or tubules as a result of dSDS induced spontaneous curvature; kinetic data from the CH region provided further evidence. Comparable data was obtained for POPE and egg-SM which showed very similar dSDS partitioning and rinsing kinetics, although the equilibrium behaviour differed in the strength of the dSDS lipid interaction. Less dSDS partitioned into the 1:1:1 mixture of POPE, egg-SM and cholesterol than any of the other species studied indicating its detergent resistance. Partial removal of this SLB from the interface left the contour of the CH region unchanged

ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening

Breast cancer screening policies attempt to achieve timely diagnosis by the regular screening of apparently healthy women. Various clinical decisions are needed to manage the screening process; those include: selecting the screening tests for a woman to take, interpreting the test outcomes, and deciding whether or not a woman should be referred to a diagnostic test. Such decisions are currently guided by clinical practice guidelines (CPGs), which represent a one-size-fits-all approach that are designed to work well on average for a population, without guaranteeing that it will work well uniformly over that population. Since the risks and benefits of screening are functions of each patients features, personalized screening policies that are tailored to the features of individuals are needed in order to ensure that the right tests are recommended to the right woman. In order to address this issue, we present ConfidentCare: a computer-aided clinical decision support system that learns a personalized screening policy from the electronic health record (EHR) data. ConfidentCare operates by recognizing clusters of similar patients, and learning the best screening policy to adopt for each cluster. A cluster of patients is a set of patients with similar features (e.g. age, breast density, family history, etc.), and the screening policy is a set of guidelines on what actions to recommend for a woman given her features and screening test scores. ConfidentCare algorithm ensures that the policy adopted for every cluster of patients satisfies a predefined accuracy requirement with a high level of confidence. We show that our algorithm outperforms the current CPGs in terms of cost-efficiency and false positive rates