HpMC: An Energy- Aware Management System for Multi-Level Memory Architectures

DRAM technology faces density and power challenges to increase capacity because of limitations of physical cell design. To overcome these limitations, system designers are exploring alternative solutions that combine DRAM and emerging NVRAM technologies. Previous work on heterogeneous memories focuses, mainly, on two system designs: PCache, a hierarchical, inclusive memory system, and HRank, a flat, non-inclusive memory system. We demonstrate that neither of these designs can universally achieve high performance and energy efficiency across a suite of HPC workloads. In this work, we investigate the impact of a number of multilevel memory designs on the performance, power, and energy consumption of applications. To achieve this goal and overcome the limited number of available tools to study heterogeneous memories, we created HMsim, an infrastructure that enables n-level, heterogeneous memory studies by leveraging existing memory simulators. We, then, propose HpMC, a new memory controller design that combines the best aspects of existing management policies to improve performance and energy. Our energy-aware memory management system dynamically switches between PCache and HRank based on the temporal locality of applications. Our results show that HpMC reduces energy consumption from 13% to 45% compared to PCache and HRank, while providing the same bandwidth and higher capacity than a conventional DRAM system.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.

A 1-D radial vaneless diffuser model accounting for the effects of aerodynamic blockage

The radial vaneless diffuser, though comparatively simple in terms of geometry, poses a significant challenge in obtaining an accurate 1-D based performance prediction due to the swirling, unsteady and distorted nature of the flow field. Turbocharger compressors specifically, with the ever increasing focus on achieving a wide operating range, have been recognised to operate with significant regions of spanwise separated flow, particularly at off-design conditions.

Using a combination of single passage Computational Fluid Dynamics (CFD) simulations and extensive gas stand test data for three geometries, the current study aims to evaluate the onset and impact of spanwise aerodynamic blockage in radial vaneless diffusers, and how the extent of the blocked region throughout the diffuser varies with both geometry and operating condition. Having analysed the governing performance parameters and flow phenomena, a novel 1-D modelling method is presented and compared to an existing baseline method as well as test data to quantify the improvement in prediction accuracy achieved.

An Investigation Into Improving Off-Design Performance in a Turbocharger Turbine Utilizing Non-Radial Blading

Off-design performance now plays a vital role in the design decisions made for automotive turbocharger turbines. Of particular interest is extracting more energy at high pressure ratios and lower rotational speeds. In this region of operation the U/C value will be low and the rotor will experience high values of positive incidence at the inlet. The positive incidence causes flow to separate on the suction surface and produces high blade loading at inlet, which drives tip leakage. A CFD analysis has been carried out on a number of automotive turbines utilizing non-radial fibred blading. To help improve secondary flows yet meet stress requirements a number of designs have been investigated. The inlet blade angle has been modified in a number of ways. Firstly, the blading has been adjusted as to provide a constant back swept angle in the span wise direction. Using the results of the constant back swept blading studies, the back swept blade angle was then varied in the span wise direction. In addition to this, in an attempt to avoid an increase in stress, the effect of varying the leading edge profile of the blade was investigated. It has been seen that off-design performance is improved by implementing back swept blading at the inlet. Varying the inlet angle in the span wise direction provided more freedom for meeting stress requirements and reduces the negative impact on blade performance at the design point. The blade leading edge profile was seen to offer small improvements during off-design operation with minimal effects on stress within the rotor. However, due to the more pointed nature of the leading edge, the rotor was less tolerant to flow misalignment at the design point.

Optimised Multiplication Architectures for Accelerating Fully Homomorphic Encryption

Large integer multiplication is a major performance bottleneck in fully homomorphic encryption (FHE) schemes over the integers. In this paper two optimised multiplier architectures for large integer multiplication are proposed. The first of these is a low-latency hardware architecture of an integer-FFT multiplier. Secondly, the use of low Hamming weight (LHW) parameters is applied to create a novel hardware architecture for large integer multiplication in integer-based FHE schemes. The proposed architectures are implemented, verified and compared on the Xilinx Virtex-7 FPGA platform. Finally, the proposed implementations are employed to evaluate the large multiplication in the encryption step of FHE over the integers. The analysis shows a speed improvement factor of up to 26.2 for the low-latency design compared to the corresponding original integer-based FHE software implementation. When the proposed LHW architecture is combined with the low-latency integer-FFT accelerator to evaluate a single FHE encryption operation, the performance results show that a speed improvement by a factor of approximately 130 is possible.

On the performance of LDPC and turbo decoder architectures with unreliable memories

In this paper, we investigate the impact of faulty memory bit-cells on the performance of LDPC and Turbo channel decoders based on realistic memory failure models. Our study investigates the inherent error resilience of such codes to potential memory faults affecting the decoding process. We develop two mitigation mechanisms that reduce the impact of memory faults rather than correcting every single error. We show how protection of only few bit-cells is sufficient to deal with high defect rates. In addition, we show how the use of repair-iterations specifically helps mitigating the impact of faults that occur inside the decoder itself.

Computing probable maximum loss in catastrophe reinsurance portfolios on multi-core and many-core architectures

In the reinsurance market, the risks natural catastrophes pose to portfolios of properties must be quantified, so that they can be priced, and insurance offered. The analysis of such risks at a portfolio level requires a simulation of up to 800 000 trials with an average of 1000 catastrophic events per trial. This is sufficient to capture risk for a global multi-peril reinsurance portfolio covering a range of perils including earthquake, hurricane, tornado, hail, severe thunderstorm, wind storm, storm surge and riverine flooding, and wildfire. Such simulations are both computation and data intensive, making the application of high-performance computing techniques desirable.

In this paper, we explore the design and implementation of portfolio risk analysis on both multi-core and many-core computing platforms. Given a portfolio of property catastrophe insurance treaties, key risk measures, such as probable maximum loss, are computed by taking both primary and secondary uncertainties into account. Primary uncertainty is associated with whether or not an event occurs in a simulated year, while secondary uncertainty captures the uncertainty in the level of loss due to the use of simplified physical models and limitations in the available data. A combination of fast lookup structures, multi-threading and careful hand tuning of numerical operations is required to achieve good performance. Experimental results are reported for multi-core processors and systems using NVIDIA graphics processing unit and Intel Phi many-core accelerators.

Preoperative radial artery volume flow is predictive of arteriovenous fistula outcomes

Objective: Guidelines recommend the creation of a wrist radiocephalic arteriovenous fistula (RAVF) as initial hemodialysis vascular access. This study explored the potential of preoperative ultrasound vessel measurements to predict AVF failure to mature (FTM) in a cohort of patients with end-stage renal disease in Northern Ireland

.Methods: A retrospective analysis was performed of all patients who had preoperative ultrasound mapping of upper limb blood vessels carried out from August 2011 to December 2014 and whose AVF reached a functional outcome by March 2015.

Results: There were 152 patients (97% white) who had ultrasound mapping andan AVF functional outcome recorded; 80 (54%) had an upper arm AVF created, and 69 (46%) had a RAVF formed. Logistic regression revealed that female gender (odds ratio [OR], 2.5; 95% confidence interval [CI], 1.12-5.55; P = .025), minimum venous diameter (OR, 0.6; 95% CI, 0.39-0.95; P = .029), and RAVF (OR, 0.4; 95% CI, 0.18-0.89; P = .026) were associated with FTM. On subgroup analysis of the RAVF group, RAVFs with an arterial volume flow <50 mL/min were seven times as likely to fail as RAVFs with higher volume flows (OR, 7.0; 95% CI, 2.35-20.87; P < .001).

Conclusions: In this cohort, a radial artery flow rate <50 mL/min was associated with a sevenfold increased risk of FTM in RAVF, which to our knowledge has not been previously reported in the literature. Preoperative ultrasound mapping adds objective assessment in the clinical prediction of AVF FTM.

Designing Bare Essentials: Aldi, Lidle and the architectures of cheapness

They’re cheap. They’re in every settlement of significance in Britain, Ireland and elsewhere. We all use them but perhaps do not always admit to it. Especially, if we are architects.
Over the past decades Aldi/Lidl low cost supermarkets have escaped from middle Europe to take over large tracts of the English speaking world remaking them according to a formula of mass-produced sheds, buff-coloured cobble-lock car parks, logos in primary colours, bare-shelves and eclectic special offers. Response within architectural discourse to this phenomenon has been largely one of indifference and such places remain, perhaps reiterating Pevsner’s controversial insights into the bicycle shed, on the peripheries of what we might term architecture. This paper seeks to explore the spatial complexities of the discount supermarket and in doing so open up a discussion on the architecture of cheapness. As a road-map, it takes former managing director Dieter Brandes’ treatise on the Aldi formula, Bare Essentials: the Aldi Way to Retailing, and investigates the strategies through which economic exigencies manifest themselves in a series of spatial tactics which involve building. Central to this is the idea of architecture as system rather than form and, in Aldi/Lidl’s case, the result of a spatial network of flows. To understand the architecture of the supermarket, then, it is necessary to measure the times and spaces of supply across the scales of intersection between global and local.
Evaluating the energy, economy and precision of such systems challenges the liminal position of the commercial, the placeless and especially the cheap within architectural discourse. As is well known, architectures of mass-production and prefabrication and their origins exercised modernist thinkers such as Sigfried Giedion and Walter Gropius in the early twentieth century and has undergone a resurgence in recent times. Meanwhile, the mapping of the hitherto overlooked forms and iconography of commerce in Learning from Las Vegas (1971) was extended by Rem Koolhaas et al into an investigation of the technologies, systems and precedents of retail in the Harvard Design School Guide to Shopping, thirty years later in 2001. While obviously always a criteria for building, to find writings on architecture which explicitly celebrate cheapness as a design virtue or, indeed, even iterate the word cheap is more difficult. Walter Gropius’ essay ‘How can we build cheaper, better, more attractive houses?’ (1927), however, situates the cheap within the discussions – articulated, amongst others, by Karl Teige and Bruno Taut – surrounding the minimal dwelling and the moral benefits of absence of the 1920s and 30s.
In our contemporary age of heightened consumption, it is perhaps fitting that an architecture of bare essentials is defined in retail rather than in housing, a commercial existenzminimum where the Miesian paradox of ‘less is more’ is resold as a paradigm of ‘more for less’ in the ubiquitous yet overlooked architectures of the discount supermarket.

The VLT-FLAMES Tarantula Survey: XVIII. Classifications and radial velocities of the B-type stars

We present spectral classifications for 438 B-type stars observed as part of the VLT-FLAMES Tarantula Survey (VFTS) in the 30 Doradus region of the Large Magellanic Cloud. Radial velocities are provided for 307 apparently single stars, and for 99 targets with radial-velocity variations which are consistent with them being spectroscopic binaries. We investigate the spatial distribution of the radial velocities across the 30 Dor region, and use the results to identify candidate runaway stars. Excluding potential runaways and members of two older clusters in the survey region (SL 639 and Hodge 301), we determine a systemic velocity for 30 Dor of 271.6 ± 12.2 km s^-1 from 273 presumed single stars. Employing a 3σ criterion we identify nine candidate runaway stars (2.9% of the single stars with radial-velocity estimates). The projected rotational velocities of the candidate runaways appear to be significantly different to those of the full B-type sample, with a strong preference for either large (≥345 km s^-1) or small (≤65 km s^-1) rotational velocities. Of the candidate runaways, VFTS 358 (classified B0.5: V) has the largest differential radial velocity (-106.9 ± 16.2 km s^-1), and a preliminary atmospheric analysis finds a significantly enriched nitrogen abundance of 12 + log (N/H) ≳ 8.5. Combined with a large rotational velocity (υ_e sin i = 345 ± 22 km s^-1), this is suggestive of past binary interaction for this star.

Non-radial instabilities and progenitor asphericities in core-collapse supernovae

Since core-collapse supernova simulations still struggle to produce robust neutrino-driven explosions in 3D, it has been proposed that asphericities caused by convection in the progenitor might facilitate shock revival by boosting the activity of non-radial hydrodynamic instabilities in the post-shock region. We investigate this scenario in depth using 42 relativistic 2D simulations with multigroup neutrino transport to examine the effects of velocity and density perturbations in the progenitor for different perturbation geometries that obey fundamental physical constraints (like the anelastic condition). As a framework for analysing our results, we introduce semi-empirical scaling laws relating neutrino heating, average turbulent velocities in the gain region, and the shock deformation in the saturation limit of non-radial instabilities. The squared turbulent Mach number, 〈Ma2〉, reflects the violence of aspherical motions in the gain layer, and explosive runaway occurs for 〈Ma2〉 ≳ 0.3, corresponding to a reduction of the critical neutrino luminosity by ∼25∼25 per cent compared to 1D. In the light of this theory, progenitor asphericities aid shock revival mainly by creating anisotropic mass flux on to the shock: differential infall efficiently converts velocity perturbations in the progenitor into density perturbations δρ/ρ at the shock of the order of the initial convective Mach number Maprog. The anisotropic mass flux and ram pressure deform the shock and thereby amplify post-shock turbulence. Large-scale (ℓ = 2, ℓ = 1) modes prove most conducive to shock revival, whereas small-scale perturbations require unrealistically high convective Mach numbers. Initial density perturbations in the progenitor are only of the order of Ma2progMaprog2 and therefore play a subdominant role.