TurboSMARTS: Accurate microarchitecture simulation sampling in minutes

Recent research proposes accelerating processor microarchitecture simulation through statistical sampling. Prior simulation sampling approaches construct accurate model state for each measurement by continuously warming large microarchitectural structures (e.g., caches and the branch predictor) while emulating the billions of instructions between measurements. This approach, called functional warming, occupies hours of runtime while the detailed simulation that is measured requires mere minutes. To eliminate the functional warming bottleneck, we propose TurboSMARTS, a simulation framework that stores functionally-warmed state in a library of small, reusable checkpoints. TurboSMARTS enables the creation of the thousands of checkpoints necessary for accurate sampling by storing only the subset of warmed state accessed during simulation of each brief execution window. TurboSMARTS matches the accuracy of prior simulation sampling techniques (i.e., ±3% error with 99.7% confidence), while estimating the performance of an 8-way out-of-order superscalar processor running SPEC CPU2000 in 91 seconds per benchmark, on average, using a 12 GB checkpoint library

An Evaluation of Stratified Sampling of Microarchitecture Simulations

Recent research advocates applying sampling to accelerate microarchitecture simulation. Simple random sampling offers accurate performance estimates (with a high quantifiable confidence) by taking a large number (e.g., 10,000) of short performance measurements over the full length of a benchmark. Simple random sampling does not exploit the often repetitive behaviors of benchmarks, collecting many redundant measurements. By identifying repetitive behaviors, we can apply stratified random sampling to achieve the same confidence as simple random sampling with far fewer measurements. Our oracle limit study of optimal stratified sampling of SPEC2K benchmarks demonstrates an opportunity to reduce required measurement by 43x over simple random sampling. Using our oracle results as a basis for comparison, we evaluate two practical approaches for selecting strata, program phase detection and IPC profiling. Program phase detection is attractive because it is microarchitec- ture independent, while IPC profiling directly minimizes stratum variance, therefore minimizing sample size. Unfortunately, our results indicate that: (1) program phase stratification falls far short of optimal opportunity, (2) IPC profiling requires expensive microarchitecture- specific analysis, and (3) both methods require large sampling unit sizes to make strata selection feasible, offsetting reductions in sample size. We conclude that, without better stratification approaches, stratified sampling does not provide a clear advantage over simple random sampling

Simulation sampling with live-points

Current simulation-sampling techniques construct accurate model state for each measurement by continuously warming large microarchitectural structures (e.g., caches and the branch predictor) while functionally simulating the billions of instructions between measurements. This approach, called functional warming, is the main performance bottleneck of simulation sampling and requires hours of runtime while the detailed simulation of the sample requires only minutes. Existing simulators can avoid functional simulation by jumping directly to particular instruction stream locations with architectural state checkpoints. To replace functional warming, these checkpoints must additionally provide microarchitectural model state that is accurate and reusable across experiments while meeting tight storage constraints. In this paper, we present a simulation-sampling framework that replaces functional warming with live-points without sacrificing accuracy. A live-point stores the bare minimum of functionally-warmed state for accurate simulation of a limited execution window while placing minimal restrictions on microarchitectural configuration. Live-points can be processed in random rather than program order, allowing simulation results and their statistical confidence to be reported while simulations are in progress. Our framework matches the accuracy of prior simulation-sampling techniques (i.e., ±3% error with 99.7% confidence), while estimating the performance of an 8-way out-of-order superscalar processor running SPEC CPU2000 in 91 seconds per benchmark, on average, using a 12 GB live-point librar

Lateral magnetic anisotropy superlattice out of a single (Ga,Mn)As layer

We use lithographically induced strain relaxation to periodically modulate the magnetic anisotropy in a single (Ga,Mn)As layer. This results in a lateral magnetoresistance device where two non-volatile magnetic states exist at zero external magnetic field with resistances resulting from the orientation of two lithographically defined regions in a single and contiguous layer.Comment: 5 pages, 7 figure

SimFlex: a fast, accurate, flexible full-system simulation framework for performance evaluation of server architecture

The new focus on commercial workloads in simulation studies of server systems has caused a drastic increase in the complexity and decrease in the speed of simulation tools. The complexity of a large-scale full-system model makes development of a monolithic simulation tool a prohibitively difficult task. Furthermore, detailed full-system models simulate so slowly that experimental results must be based on simulations of only fractions of a second of execution of the modelled system. This paper presents SimFlex, a simulation framework which uses component-based design and rigorous statistical sampling to enable development of complex models and ensure representative measurement results with fast simulation turnaround. The novelty of SimFlex lies in its combination of a unique, compile-time approach to component interconnection and a methodology for obtaining accurate results from sampled simulations on a platform capable of evaluating unmodified commercial workload

Cognitive and memory training in adults at risk of dementia: A Systematic Review

<p>Abstract</p> <p>Background</p> <p>Effective non-pharmacological cognitive interventions to prevent Alzheimer's dementia or slow its progression are an urgent international priority. The aim of this review was to evaluate cognitive training trials in individuals with mild cognitive impairment (MCI), and evaluate the efficacy of training in memory strategies or cognitive exercises to determine if cognitive training could benefit individuals at risk of developing dementia.</p> <p>Methods</p> <p>A systematic review of eligible trials was undertaken, followed by effect size analysis. Cognitive training was differentiated from other cognitive interventions not meeting generally accepted definitions, and included both cognitive exercises and memory strategies.</p> <p>Results</p> <p>Ten studies enrolling a total of 305 subjects met criteria for cognitive training in MCI. Only five of the studies were randomized controlled trials. Meta-analysis was not considered appropriate due to the heterogeneity of interventions. Moderate effects on memory outcomes were identified in seven trials. Cognitive exercises (relative effect sizes ranged from .10 to 1.21) may lead to greater benefits than memory strategies (.88 to -1.18) on memory.</p> <p>Conclusions</p> <p>Previous conclusions of a lack of efficacy for cognitive training in MCI may have been influenced by not clearly defining the intervention. Our systematic review found that cognitive exercises can produce moderate-to-large beneficial effects on memory-related outcomes. However, the number of high quality RCTs remains low, and so further trials must be a priority. Several suggestions for the better design of cognitive training trials are provided.</p

Host, Suppressor, and Promoter The Roles of Ni and Fe on Oxygen Evolution Reaction Activity and Stability of NiFe Alloy Thin Films in Alkaline Media

Understanding the oxygen evolution reaction OER activity and stability of the NiFe based materials is important for achieving low cost and highly efficient electrocatalysts for practical water splitting. Here, we report the roles of Ni and Fe on the OER activity and stability of metallic NiFe and pure Ni thin films in alkaline media. Our results support that Ni OH 2 NiOOH does not contribute to the OER directly, but it serves as an ideal host for Fe incorporation, which is essential for obtaining high OER activity. Furthermore, the availability of Fe in the electrolyte is found to be important and necessary for both NiFe and pure Ni thin films to maintain an enhanced OER performance, while the presence of Ni is detrimental to the OER kinetics. The impacts of Fe and Ni species present in KOH on the OER activity are consistent with the dissolution re deposition mechanism we proposed. Stability studies show that the OER activity will degrade under prolonged continuous operation. Satisfactory stability can, however, be achieved with intermittent OER operation, in which the electrocatalyst is cycled between degraded and recovered states. Accordingly, two important ranges, that is, the recovery range and the degradation range, are proposed. Compared to the intermittent OER operation, prolonged continuous OER operation i.e., in the degradation range generates a higher NiOOH content in the electrocatalyst, which is likely related to the OER deactivation. If the electrode works in the recovery range for a certain period, that is, at a sufficiently low reduction potential, where Ni3 is reduced to Ni2 , the OER activity can be maintained and even improved if Fe is also present in the electrolyt

Pentoxifylline as an adjunct therapy in children with cerebral malaria

<p>Abstract</p> <p>Background</p> <p>Pentoxifylline (PTX) affects many processes that may contribute to the pathogenesis of severe malaria and it has been shown to reduce the duration of coma in children with cerebral malaria. This pilot study was performed to assess pharmacokinetics, safety and efficacy of PTX in African children with cerebral malaria.</p> <p>Methods</p> <p>Ten children admitted to the high dependency unit of the Kilifi District Hospital in Kenya with cerebral malaria (Blantyre coma score of 2 or less) received quinine plus a continuous infusion of 10 mg/kg/24 hours PTX for 72 hours. Five children were recruited as controls and received normal saline instead of PTX. Plasma samples were taken for PTX and tumour necrosis factor (TNF) levels. Blantyre Coma Score, parasitemia, hematology and vital signs were assessed 4 hourly.</p> <p>Results</p> <p>One child (20%) in the control group died, compared to four children (40%) in the PTX group. This difference was not significant (p = 0.60). Laboratory parameters and clinical data were comparable between groups. TNF levels were lower in children receiving PTX.</p> <p>Conclusions</p> <p>The small sample size does not permit definitive conclusions, but the mortality rate was unexpectedly high in the PTX group.</p

Comparative assessment of clinical rating scales in Wilson’s disease

Background: Wilson’s disease (WD) is an autosomal recessive disorder of copper metabolism resulting in multifaceted neurological, hepatic, and psychiatric symptoms. The objective of the study was to comparatively assess two clinical rating scales for WD, the Unified Wilson’s Disease Rating Scale (UWDRS) and the Global Assessment Scale for Wilson’s disease (GAS for WD), and to test the feasibility of the patient reported part of the UWDRS neurological subscale (termed the “minimal UWDRS”). Methods: In this prospective, monocentric, cross-sectional study, 65 patients (median age 35 [range: 15–62] years; 33 female, 32 male) with treated WD were scored according to the two rating scales. Results: The UWDRS neurological subscore correlated with the GAS for WD Tier 2 score (r = 0.80; p < 0.001). Correlations of the UWDRS hepatic subscore and the GAS for WD Tier 1 score with both the Model for End Stage Liver Disease (MELD) score (r = 0.44/r = 0.28; p < 0.001/p = 0.027) and the Child-Pugh score (r = 0.32/r = 0.12; p = 0.015/p = 0.376) were weak. The “minimal UWDRS” score significantly correlated with the UWDRS total score (r = 0.86), the UWDRS neurological subscore (r = 0.89), and the GAS for WD Tier 2 score (r = 0.86). Conclusions: The UWDRS neurological and psychiatric subscales and the GAS for WD Tier 2 score are valuable tools for the clinical assessment of WD patients. The “minimal UWDRS” is a practical prescreening tool outside scientific trials