bluuebunny/crossref_metadata_2025 huggingface dataset:
Low Wavenumber Raman Modes and Plasmon Resonance in Cd Nanoparticles Obtained in Extract of Opuntia Ficus-Indica Plant
Authors: Cortez-Valadez M. , Ramírez-Rodríguez L. P. , Bocarando-Chacon J.-G. , Flores-Acosta M. , Velumani S. , Ramírez-Bon R.
Published: June 2015

Cadmium colloidal crystalline nanoparticles were obtained by a simple green synthesis method employing the plant extract of Opuntia ficus-indica. The plant extract reduces the Cd ions and stabilizes the size of cadmium colloidal particles at the nanometric level. The size and morphology of agglomerates of nanoparticles of about 100 nm were analyzed by field-emission scanning electron microscopy (FESEM). The size, shape and crystalline structure of the Cd nanoparticles were determined from TEM analysis. The results show that Cd nanoparticles with hexagonal crystalline structure and average size 2–3 nm were obtained by this green synthesis method. The optical absorption spectrum of the colloidal solution containing the cadmium nanoparticles displays an optical absorption band centered at 236 nm, which was attributed to the plasmon resonance of the Cd colloidal nanoparticles. Mie theory for colloidal systems was applied to reproduce theoretically the plasmon resonance absorption data of the Cd colloidal nanoparticles. Furthermore, the Raman spectrum of powder from dried samples after reduction of cadmium ions, displays a low wavenumber vibration mode centered at 114 cm-1, assigned to the Cd nanoparticles. Density functional theory (DFT) calculations at local spin density approximation (LSDA) level were performed to determine the structure and vibrational properties of small clusters of cadmium consisting of 3–10 atoms. Radial breathing modes with frequencies between 90 cm-1 and 120 cm-1 were found to be the most active Raman modes of the low-energy Cd n clusters.
Could a Less Developed City Solve Its CO2 Emission Dilemma? Evidence from a Low Carbon Pilot City
Authors: JIANG Wei
Published: June 2015

Facing up to the global warming, China has addressed great efforts on low carbon development. Since the year 2010, it has issued two batches of low carbon pilots. However, not all the pilots produced satisfactory outcomes as expected, while a less developed pilot city, Guangyuan got a reassuring result which was considered as a surprise. How do we explain this surprise? Could a less developed city solve its CO 2 emission dilemma while pursuing the industrialization and urbanization? Using sequential game and multi-case comparison, this paper tries to examine the main drivers of Guangyuan's low carbon initiative and the determinants of its achievement. The analysis shows that Guangyuan had no advantages in low carbon potential compared with its reference cities, while the low carbon surprise was due to its strong political willingness and leadership, an effective multi-level governance network and a low carbon oriented evaluation system for local officials. It demonstrates that a less developed city could solve the CO 2 emission dilemma while seeking its economic growth; technical level, fund, and human resources are important but not dominant; to ensure the implementation of low carbon policies, meeting low carbon objectives should be taken full consideration into the evaluation system for local officials.
Biological Oxygen Demand and Economic Growth: An Empirical Investigation
Authors: Joshi Prathibha , Beck Kris Aaron
Published: June 2015

Economic development frequently contributes to a decline in water quality; industrial effluents entering the water cause an increase of bacteria that strip the water of its oxygen, often then leading to mass die-offs of other aquatic life. However, the environmental Kuznets curve (EKC) suggests that rising water pollution due to continuing economic growth ultimately stabilizes and then decreases, thus eventually resulting in more oxygenated water that can meet the biological oxygen demand (BOD) required by aquatic life. Yet previous studies have found mixed results for a BOD EKC, with some researchers confirming the inverted U scale of the EKC but others finding different patterns. We therefore re-evaluate the interaction between economic growth and water quality by using a balanced dataset from 1979–1995 and the more dynamic econometric technique of Arellano–Bover/Blundell–Bond generalized methods of moments (GMM) estimator. We compare different samples of OECD and non-OECD countries to determine the likelihood of an EKC. The results show that the OECD countries have an N-shaped curve and that the EKC only emerges with a general sample of non-OECD countries.
How subduction broke up Pangaea with implications for the supercontinent cycle
Authors: Keppie Fraser
Published: June 2015

Mechanisms that can explain the Mesozoic motion of Pangaea in a palaeomagnetic mantle reference frame may also be able to explain its breakup. Calculations indicate that Pangaea moved along a non-rigid path in the mantle frame between the late Triassic and early Jurassic. The breakup of Pangaea may have happened as a response to this non-rigid motion. Tectonic forces applied to the margins of Pangaea as a consequence of subduction at its peripheries can explain both the motion and deformation of Pangaea with a single mechanism. In contrast, mantle forces applied to the base of Pangaea appear to be inconsistent with the kinematic constraints and do not explain the change in supercontinent motion that accompanied the breakup event. Top-down plate tectonics are inferred to have caused the breakup of Pangaea. Strong coupling between the mantle and lithosphere may not have been the case during the Phanerozoic eon when the Pangaean supercontinent formed and subsequently dispersed.
Ubiquity symposium 'What is computation?'
Authors: Conery John S.
Published: June 2015

In the second in the series of articles in the Ubiquity Symposium What is Computation?, Prof. John S. Conery of the University of Oregon explains why he believes computation can be seen as symbol manipulation. For more articles in this series, see table of contents in the http://ubiquity.acm.org/article.cfm?id=1870596 Editors Introduction to the symposium. --Editor
Numerical Integration of Discontinuous Functions in Many Dimensions
Authors: Pandis Vassilis
Published: June 2015

We consider the problem of numerically integrating functions with hyperplane discontinuities over the entire Euclidean space in many dimensions. We describe a simple process through which the Euclidean space is partitioned into simplices on which the integrand is smooth, generalising the standard practice of dividing the interval used in one-dimensional problems. Our procedure is combined with existing adaptive cubature algorithms to significantly reduce the necessary number of function evaluations and memory requirements of the integrator. The method is embarrassingly parallel and can be trivially scaled across many cores with virtually no overhead. Our method is particularly pertinent to the integration of Green's functions, a problem directly related to the perturbation theory of impurity models. In three spatial dimensions, we observe a speed-up of order 100 which increases with increasing dimensionality.
Sustainable Making? Balancing Optimism and Criticism in HCI Discourse
Authors: Roedl David , Bardzell Shaowen , Bardzell Jeffrey
Published: June 2015

We examine the recent move from a rhetoric of “users” toward one of “makers,” “crafters,” and “hackers” within HCI discourse. Through our analysis, we make several contributions. First, we provide a general overview of the structure and common framings within research on makers. We discuss how these statements reconfigure themes of empowerment and progress that have been central to HCI rhetoric since the field's inception. In the latter part of the article, we discuss the consequences of these shifts for contemporary research problems. In particular, we explore the problem of designed obsolescence, a core issue for Sustainable Interaction Design (SID) research. We show how the framing of the maker, as an empowered subject, presents certain opportunities and limitations for this research discourse. Finally, we offer alternative framings of empowerment that can expand maker discourse and its use in contemporary research problems such as SID.
Information Measures in Statistical Privacy and Data Processing Applications
Authors: Lin Bing-Rong , Kifer Daniel
Published: June 2015

In statistical privacy,
utility
refers to two concepts:
information preservation,
how much statistical information is retained by a sanitizing algorithm, and
usability,
how (and with how much difficulty) one extracts this information to build statistical models, answer queries, and so forth. Some scenarios incentivize a separation between information preservation and usability, so that the data owner first chooses a sanitizing algorithm to maximize a measure of information preservation, and, afterward, the data consumers process the sanitized output according to their various individual needs [Ghosh et al. 2009; Williams and McSherry 2010].

We analyze the information-preserving properties of utility measures with a combination of two new and three existing utility axioms and study how violations of an axiom can be fixed. We show that the average (over possible outputs of the sanitizer) error of Bayesian decision makers forms the unique class of utility measures that satisfy all of the axioms. The axioms are agnostic to Bayesian concepts such as subjective probabilities and hence strengthen support for Bayesian views in privacy research. In particular, this result connects information preservation to aspects of usability—if the information preservation of a sanitizing algorithm should be measured as the average error of a Bayesian decision maker, shouldn’t Bayesian decision theory be a good choice when it comes to using the sanitized outputs for various purposes? We put this idea to the test in the unattributed histogram problem where our decision-theoretic postprocessing algorithm empirically outperforms previously proposed approaches.
Adding Human Learning in Brain--Computer Interfaces (BCIs)
Authors: Kosmyna Nataliya , Tarpin-Bernard Franck , Rivet Bertrand
Published: June 2015

In this article, we introduce CLBCI (Co-Learning for Brain--Computer Interfaces), a BCI architecture based on co-learning in which users can give explicit feedback to the system rather than just receiving feedback. CLBCI is based on minimum distance classification with Independent Component Analysis (ICA) and allows for shorter training times compared to classical BCIs, as well as faster learning in users and a good performance progression. We further propose a new scheme for real-time two-dimensional visualization of classification outcomes using Wachspress coordinate interpolation. It allows us to represent classification outcomes for n classes in simple regular polygons. Our objective is to devise a BCI system that constitutes a practical interaction modality that can be deployed rapidly and used on a regular basis. We apply our system to an event-based control task in the form of a simple shooter game in which we evaluate the learning effect induced by our architecture compared to a classical approach. We also evaluate how much user feedback and our visualization method contribute to the performance of the system.
Improving Top-N Recommendation for Cold-Start Users via Cross-Domain Information
Authors: Mirbakhsh Nima , Ling Charles X.
Published: June 2015

Making accurate recommendations for cold-start users is a challenging yet important problem in recommendation systems. Including more information from other domains is a natural solution to improve the recommendations. However, most previous work in cross-domain recommendations has focused on improving prediction accuracy with several severe limitations. In this article, we extend our previous work on clustering-based matrix factorization in single domains into cross domains. In addition, we utilize recent results on unobserved ratings. Our new method can more effectively utilize data from auxiliary domains to achieve better recommendations, especially for cold-start users. For example, our method improves the recall to 21% on average for cold-start users, whereas previous methods result in only 15% recall in the cross-domain Amazon dataset. We also observe almost the same improvements in the Epinions dataset. Considering that it is often difficult to make even a small improvement in recommendations, for cold- start users in particular, our result is quite significant.
Chromatic Correlation Clustering
Authors: Bonchi Francesco , Gionis Aristides , Gullo Francesco , Tsourakakis Charalampos E. , Ukkonen Antti
Published: June 2015

We study a novel clustering problem in which the pairwise relations between objects are
categorical
. This problem can be viewed as clustering the vertices of a graph whose edges are of different types (
colors
). We introduce an objective function that ensures the edges within each cluster have, as much as possible, the same color. We show that the problem is
NP
-hard and propose a randomized algorithm with approximation guarantee proportional to the maximum degree of the input graph. The algorithm iteratively picks a random edge as a pivot, builds a cluster around it, and removes the cluster from the graph. Although being fast, easy to implement, and parameter-free, this algorithm tends to produce a relatively large number of clusters. To overcome this issue we introduce a variant algorithm, which modifies how the pivot is chosen and how the cluster is built around the pivot. Finally, to address the case where a fixed number of output clusters is required, we devise a third algorithm that directly optimizes the objective function based on the
alternating-minimization
paradigm.

We also extend our objective function to handle cases where object’s relations are described by multiple labels. We modify our randomized approximation algorithm to optimize such an extended objective function and show that its approximation guarantee remains proportional to the maximum degree of the graph.

We test our algorithms on synthetic and real data from the domains of social media, protein-interaction networks, and bibliometrics. Results reveal that our algorithms outperform a baseline algorithm both in the task of reconstructing a ground-truth clustering and in terms of objective-function value.
Investigating Information Search by People with Cognitive Disabilities
Authors: Hu Ruimin , Feng Jinjuan Heidi
Published: June 2015

The ability to gather information online has become increasingly important in the past decades. Previous research suggests that people with cognitive disabilities experience challenges when finding information on websites. Although a number of studies examined the impact of various design guidelines on information search by people with cognitive disabilities, our knowledge in this topic remains limited. To date, no study has been conducted to examine how people with cognitive disabilities navigate in different content structures. We completed an empirical study to investigate the impact of different search methods and content structures on the search behavior of people with cognitive disabilities. 23 participants with various cognitive disabilities completed 15 information search tasks under three conditions: browsing a website with a deep structure (4 × 4 × 4 × 4), browsing a website with a broad structure (16 × 16), and searching through a search engine. The results suggest that the participants overwhelmingly preferred the search engine method to the two browsing conditions. The broad structure resulted in significantly higher failure rates than the search engine condition and the deep structure condition. The causes of failed search tasks were analyzed in detail. Participants frequently visited incorrect categories in both the deep structure and the broad structure conditions. However, it was more difficult to recover from incorrect categories on the lower-level pages in the broad structure than in the deep structure. Under the search engine condition, failed tasks were mainly caused by difficulty in selecting the correct link from the returned list, misspellings, and difficulty in generating appropriate search keywords.
Misbehavior in Bitcoin
Authors: Karame Ghassan O. , Androulaki Elli , Roeschlin Marc , Gervais Arthur , Čapkun Srdjan
Published: June 2015

Bitcoin is a decentralized payment system that relies on Proof-of-Work (PoW) to resist double-spending through a distributed timestamping service. To ensure the operation and security of Bitcoin, it is essential that all transactions and their order of execution are available to all Bitcoin users.

Unavoidably, in such a setting, the security of transactions comes at odds with transaction privacy. Motivated by the fact that transaction confirmation in Bitcoin requires tens of minutes, we analyze the conditions for performing successful double-spending attacks against fast payments in Bitcoin, where the time between the exchange of currency and goods is short (in the order of a minute). We show that unless new detection techniques are integrated in the Bitcoin implementation, double-spending attacks on fast payments succeed with considerable probability and can be mounted at low cost. We propose a new and lightweight countermeasure that enables the detection of double-spending attacks in fast transactions.

In light of such misbehavior, accountability becomes crucial. We show that in the specific case of Bitcoin, accountability complements privacy. To illustrate this tension, we provide accountability and privacy definition for Bitcoin, and we investigate analytically and empirically the privacy and accountability provisions in Bitcoin.
Editorial
Authors: Heroux Michael A.
Published: June 2015

The scientific community relies on the peer review process for assuring the quality of published material, the goal of which is to build a body of work we can trust. Computational journals such as the
ACM Transactions on Mathematical Software
(TOMS) use this process for rigorously promoting the clarity and completeness of content, and citation of prior work. At the same time, it is unusual to independently confirm computational results.

ACM TOMS has established a
Replicated Computational Results
(RCR) review process as part of the manuscript peer review process. The purpose is to provide independent confirmation that results contained in a manuscript are replicable. Successful completion of the RCR process awards a manuscript with the Replicated Computational Results Designation.

This issue of ACM TOMS contains the first [Van Zee and van de Geijn 2015] of what we anticipate to be a growing number of articles to receive the RCR designation, and the related RCR reviewer report [Willenbring 2015]. We hope that the TOMS RCR process will serve as a model for other publications and increase the confidence in and value of computational results in TOMS articles.
The Cameraman Operating My Virtual Camera is Artificial
Authors: Gaddam Vamsidhar Reddy , Eg Ragnhild , Langseth Ragnar , Griwodz Carsten , Halvorsen Pål
Published: June 2015

In this article, we argue that the energy spent in designing autonomous camera control systems is not spent in vain. We present a real-time virtual camera system that can create
smooth
camera motion. Similar systems are frequently benchmarked with the human operator as the best possible reference; however, we avoid a priori assumptions in our evaluations. Our main question is simply whether we can design algorithms to steer a virtual camera that can compete with the user experience for recordings from an expert operator with several years of experience? In this respect, we present two low-complexity servoing methods that are explored in two user studies. The results from the user studies give a promising answer to the question pursued. Furthermore, all components of the system meet the real-time requirements on commodity hardware. The growing capabilities of both hardware and network in mobile devices give us hope that this system can be deployed to mobile users in the near future. Moreover, the design of the presented system takes into account that services to concurrent users must be supported.
Weakening Cardinality Constraints Creates Harder Satisfiability Benchmarks
Authors: Spence Ivor
Published: June 2015

For some time, the satisfiability formulae that have been the most difficult to solve for their size have been crafted to be unsatisfiable by the use of cardinality constraints. Recent solvers have introduced explicit checking of such constraints, rendering previously difficult formulae trivial to solve. A family of unsatisfiable formulae is described that is derived from the sgen4 family but cannot be solved using cardinality constraints detection and reasoning alone. These formulae were found to be the most difficult during the SAT2014 competition by a significant margin and include the shortest unsolved benchmark in the competition, sgen6-1200-5-1.cnf.
FACADE
Authors: Nguyen Khanh , Wang Kai , Bu Yingyi , Fang Lu , Hu Jianfei , Xu Guoqing
Published: June 2015

The past decade has witnessed the increasing demands on data-driven business intelligence that led to the proliferation of data-intensive applications. A managed object-oriented programming language such as Java is often the developer's choice for implementing such applications, due to its quick development cycle and rich community resource. While the use of such languages makes programming easier, their automated memory management comes at a cost. When the managed runtime meets Big Data, this cost is significantly magnified and becomes a scalability-prohibiting bottleneck. This paper presents a novel compiler framework, called Facade, that can generate highly-efficient data manipulation code by automatically transforming the data path of an existing Big Data application. The key treatment is that in the generated code, the number of runtime heap objects created for data types in each thread is (almost) statically bounded, leading to significantly reduced memory management cost and improved scalability. We have implemented Facade and used it to transform 7 common applications on 3 real-world, already well-optimized Big Data frameworks: GraphChi, Hyracks, and GPS. Our experimental results are very positive: the generated programs have (1) achieved a 3%--48% execution time reduction and an up to 88X GC reduction; (2) consumed up to 50% less memory, and (3) scaled to much larger datasets.
Synchronization Using Remote-Scope Promotion
Authors: Orr Marc S. , Che Shuai , Yilmazer Ayse , Beckmann Bradford M. , Hill Mark D. , Wood David A.
Published: June 2015

Heterogeneous system architecture (HSA) and OpenCL define scoped synchronization to facilitate low overhead communication across a subset of threads. Scoped synchronization works well for static sharing patterns, where consumer threads are known a priori. It works poorly for dynamic sharing patterns (e.g., work stealing) where programmers cannot use a faster small scope due to the rare possibility that the work is stolen by a thread in a distant slower scope. This puts programmers in a conundrum: optimize the common case by synchronizing at a faster small scope or use work stealing at a slower large scope. In this paper, we propose to extend scoped synchronization with remote-scope promotion. This allows the most frequent sharers to synchronize through a small scope. Infrequent sharers synchronize by promoting that remote small scope to a larger shared scope. Synchronization using remote-scope promotion provides performance robustness for dynamic workloads, where the benefits provided by scoped synchronization and work stealing are hard to anticipate. Compared to a naïve baseline, static scoped synchronization alone achieves a 1.07x speedup on average and dynamic work stealing alone achieves a 1.18x speedup on average. In contrast, synchronization using remote-scope promotion achieves a robust 1.25x speedup on average, across a diverse set of graph benchmarks and inputs.
rIOMMU
Authors: Malka Moshe , Amit Nadav , Ben-Yehuda Muli , Tsafrir Dan
Published: June 2015

The IOMMU allows the OS to encapsulate I/O devices in their own virtual memory spaces, thus restricting their DMAs to specific memory pages. The OS uses the IOMMU to protect itself against buggy drivers and malicious/errant devices. But the added protection comes at a cost, degrading the throughput of I/O-intensive workloads by up to an order of magnitude. This cost has motivated system designers to trade off some safety for performance, e.g., by leaving stale information in the IOTLB for a while so as to amortize costly invalidations. We observe that high-bandwidth devices---like network and PCIe SSD controllers---interact with the OS via circular ring buffers that induce a sequential, predictable workload. We design a ring IOMMU (rIOMMU) that leverages this characteristic by replacing the virtual memory page table hierarchy with a circular, flat table. A flat table is adequately supported by exactly one IOTLB entry, making every new translation an implicit invalidation of the former and thus requiring explicit invalidations only at the end of I/O bursts. Using standard networking benchmarks, we show that rIOMMU provides up to 7.56x higher throughput relative to the baseline IOMMU, and that it is within 0.77--1.00x the throughput of a system without IOMMU protection.
DeNovoSync
Authors: Sung Hyojin , Adve Sarita V.
Published: June 2015

Current shared-memory hardware is complex and inefficient. Prior work on the DeNovo coherence protocol showed that disciplined shared-memory programming models can enable more complexity-, performance-, and energy-efficient hardware than the state-of-the-art MESI protocol. DeNovo, however, severely restricted the synchronization constructs an application can support. This paper proposes DeNovoSync, a technique to support arbitrary synchronization in DeNovo. The key challenge is that DeNovo exploits race-freedom to use reader-initiated local self-invalidations (instead of conventional writer-initiated remote cache invalidations) to ensure coherence. Synchronization accesses are inherently racy and not directly amenable to self-invalidations. DeNovoSync addresses this challenge using a novel combination of registration of all synchronization reads with a judicious hardware backoff to limit unnecessary registrations. For a wide variety of synchronization constructs and applications, compared to MESI, DeNovoSync shows comparable or up to 22% lower execution time and up to 58% lower network traffic, enabling DeNovo's advantages for a much broader class of software than previously possible.
Compiler Management of Communication and Parallelism for Quantum Computation
Authors: Heckey Jeff , Patil Shruti , JavadiAbhari Ali , Holmes Adam , Kudrow Daniel , Brown Kenneth R. , Franklin Diana , Chong Frederic T. , Martonosi Margaret
Published: June 2015

Quantum computing (QC) offers huge promise to accelerate a range of computationally intensive benchmarks. Quantum computing is limited, however, by the challenges of decoherence: i.e., a quantum state can only be maintained for short windows of time before it decoheres. While quantum error correction codes can protect against decoherence, fast execution time is the best defense against decoherence, so efficient architectures and effective scheduling algorithms are necessary. This paper proposes the Multi-SIMD QC architecture and then proposes and evaluates effective schedulers to map benchmark descriptions onto Multi-SIMD architectures. The Multi-SIMD model consists of a small number of SIMD regions, each of which may support operations on up to thousands of qubits per cycle.

Efficient Multi-SIMD operation requires efficient scheduling. This work develops schedulers to reduce communication requirements of qubits between operating regions, while also improving parallelism.We find that communication to global memory is a dominant cost in QC. We also note that many quantum benchmarks have long serial operation paths (although each operation may be data parallel). To exploit this characteristic, we introduce Longest-Path-First Scheduling (LPFS) which pins operations to SIMD regions to keep data in-place and reduce communication to memory. The use of small, local scratchpad memories also further reduces communication. Our results show a 3% to 308% improvement for LPFS over conventional scheduling algorithms, and an additional 3% to 64% improvement using scratchpad memories. Our work is the most comprehensive software-to-quantum toolflow published to date, with efficient and practical scheduling techniques that reduce communication and increase parallelism for full-scale quantum code executing up to a trillion quantum gate operations.
Automated OS-level Device Runtime Power Management
Authors: Xu Chao , Lin Felix Xiaozhu , Wang Yuyang , Zhong Lin
Published: June 2015

Non-CPU devices on a modern system-on-a-chip (SoC), ranging from accelerators to I/O controllers, account for a significant portion of the chip area. It is therefore vital for system energy efficiency that idle devices can enter a low-power state while still meeting the performance expectation. This is called device runtime Power Management (PM) for which individual device drivers in commodity OSes are held responsible today. Based on the observations of existing drivers and their evolution, we consider it harmful to rely on drivers for device runtime PM. This paper identifies three pieces of information as essential to device runtime PM, and shows that they can be obtained without involving drivers, either by using a software-only approach, or more efficiently, by adding one register bit to each device. We thus suggest a structural change to the current Linux runtime PM framework, replacing the PM code in all applicable drivers with a single kernel module called the central PM agent. Experimental evaluations show that the central PM agent is just as effective as hand-tuned driver PM code. The paper also presents a tool called PowerAdvisor that simplifies driver PM efforts under the current Linux runtime PM framework. PowerAdvisor analyzes execution traces and suggests where to insert PM calls in driver source code. Despite being a best-effort tool, PowerAdvisor not only reproduces hand-tuned PM code from stock drivers, but also correctly suggests PM code never known before. Overall, our experience shows that it is promising to ultimately free driver developers from manual PM.
PolyMage
Authors: Mullapudi Ravi Teja , Vasista Vinay , Bondhugula Uday
Published: June 2015

This paper presents the design and implementation of PolyMage, a domain-specific language and compiler for image processing pipelines. An image processing pipeline can be viewed as a graph of interconnected stages which process images successively. Each stage typically performs one of point-wise, stencil, reduction or data-dependent operations on image pixels. Individual stages in a pipeline typically exhibit abundant data parallelism that can be exploited with relative ease. However, the stages also require high memory bandwidth preventing effective utilization of parallelism available on modern architectures. For applications that demand high performance, the traditional options are to use optimized libraries like OpenCV or to optimize manually. While using libraries precludes optimization across library routines, manual optimization accounting for both parallelism and locality is very tedious.

The focus of our system, PolyMage, is on automatically generating high-performance implementations of image processing pipelines expressed in a high-level declarative language. Our optimization approach primarily relies on the transformation and code generation capabilities of the polyhedral compiler framework. To the best of our knowledge, this is the first model-driven compiler for image processing pipelines that performs complex fusion, tiling, and storage optimization automatically. Experimental results on a modern multicore system show that the performance achieved by our automatic approach is up to 1.81x better than that achieved through manual tuning in Halide, a state-of-the-art language and compiler for image processing pipelines. For a camera raw image processing pipeline, our performance is comparable to that of a hand-tuned implementation.
On-the-Fly Principled Speculation for FSM Parallelization
Authors: Zhao Zhijia , Shen Xipeng
Published: June 2015

Finite State Machine (FSM) is the backbone of an important class of applications in many domains. Its parallelization has been extremely difficult due to inherent strong dependences in the computation. Recently, principled speculation shows good promise to solve the problem. However, the reliance on offline training makes the approach inconvenient to adopt and hard to apply to many practical FSM applications, which often deal with a large variety of inputs different from training inputs. This work presents an assembly of techniques that completely remove the needs for offline training. The techniques include a set of theoretical results on inherent properties of FSMs, and two newly designed dynamic optimizations for efficient FSM characterization. The new techniques, for the first time, make principle speculation applicable on the fly, and enables swift, automatic configuration of speculative parallelizations to best suit a given FSM and its current input. They eliminate the fundamental barrier for practical adoption of principle speculation for FSM parallelization. Experiments show that the new techniques give significantly higher speedups for some difficult FSM applications in the presence of input changes.
A Probabilistic Graphical Model-based Approach for Minimizing Energy Under Performance Constraints
Authors: Mishra Nikita , Zhang Huazhe , Lafferty John D. , Hoffmann Henry
Published: June 2015

In many deployments, computer systems are underutilized -- meaning that applications have performance requirements that demand less than full system capacity. Ideally, we would take advantage of this under-utilization by allocating system resources so that the performance requirements are met and energy is minimized. This optimization problem is complicated by the fact that the performance and power consumption of various system configurations are often application -- or even input -- dependent. Thus, practically, minimizing energy for a performance constraint requires fast, accurate estimations of application-dependent performance and power tradeoffs. This paper investigates machine learning techniques that enable energy savings by learning Pareto-optimal power and performance tradeoffs. Specifically, we propose LEO, a probabilistic graphical model-based learning system that provides accurate online estimates of an application's power and performance as a function of system configuration. We compare LEO to (1) offline learning, (2) online learning, (3) a heuristic approach, and (4) the true optimal solution. We find that LEO produces the most accurate estimates and near optimal energy savings.
Hybrid Static–Dynamic Analysis for Statically Bounded Region Serializability
Authors: Sengupta Aritra , Biswas Swarnendu , Zhang Minjia , Bond Michael D. , Kulkarni Milind
Published: June 2015

Data races are common. They are difficult to detect, avoid, or eliminate, and programmers sometimes introduce them intentionally. However, shared-memory programs with data races have unexpected, erroneous behaviors. Intentional and unintentional data races lead to atomicity and sequential consistency (SC) violations, and they make it more difficult to understand, test, and verify software. Existing approaches for providing stronger guarantees for racy executions add high run-time overhead and/or rely on custom hardware. This paper shows how to provide stronger semantics for racy programs while providing relatively good performance on commodity systems. A novel hybrid static--dynamic analysis called \emph{EnfoRSer} provides end-to-end support for a memory model called \emph{statically bounded region serializability} (SBRS) that is not only stronger than weak memory models but is strictly stronger than SC. EnfoRSer uses static compiler analysis to transform regions, and dynamic analysis to detect and resolve conflicts at run time. By demonstrating commodity support for a reasonably strong memory model with reasonable overheads, we show its potential as an always-on execution model.
Few-to-Many
Authors: Haque Md E. , Eom Yong hun , He Yuxiong , Elnikety Sameh , Bianchini Ricardo , McKinley Kathryn S.
Published: June 2015

Interactive services, such as Web search, recommendations, games, and finance, must respond quickly to satisfy customers. Achieving this goal requires optimizing tail (e.g., 99th+ percentile) latency. Although every server is multicore, parallelizing individual requests to reduce tail latency is challenging because (1) service demand is unknown when requests arrive; (2) blindly parallelizing all requests quickly oversubscribes hardware resources; and (3) parallelizing the numerous short requests will not improve tail latency. This paper introduces Few-to-Many (FM) incremental parallelization, which dynamically increases parallelism to reduce tail latency. FM uses request service demand profiles and hardware parallelism in an offline phase to compute a policy, represented as an interval table, which specifies when and how much software parallelism to add. At runtime, FM adds parallelism as specified by the interval table indexed by dynamic system load and request execution time progress. The longer a request executes, the more parallelism FM adds. We evaluate FM in Lucene, an open-source enterprise search engine, and in Bing, a commercial Web search engine. FM improves the 99th percentile response time up to 32% in Lucene and up to 26% in Bing, compared to prior state-of-the-art parallelization. Compared to running requests sequentially in Bing, FM improves tail latency by a factor of two. These results illustrate that incremental parallelism is a powerful tool for reducing tail latency.
Targeted Automatic Integer Overflow Discovery Using Goal-Directed Conditional Branch Enforcement
Authors: Sidiroglou-Douskos Stelios , Lahtinen Eric , Rittenhouse Nathan , Piselli Paolo , Long Fan , Kim Deokhwan , Rinard Martin
Published: June 2015

We present a new technique and system, DIODE, for auto- matically generating inputs that trigger overflows at memory allocation sites. DIODE is designed to identify relevant sanity checks that inputs must satisfy to trigger overflows at target memory allocation sites, then generate inputs that satisfy these sanity checks to successfully trigger the overflow. DIODE works with off-the-shelf, production x86 binaries. Our results show that, for our benchmark set of applications, and for every target memory allocation site exercised by our seed inputs (which the applications process correctly with no overflows), either 1) DIODE is able to generate an input that triggers an overflow at that site or 2) there is no input that would trigger an overflow for the observed target expression at that site.
Regulation of Alternative Splicing Through Coupling with Transcription and Chromatin Structure
Authors: Naftelberg Shiran , Schor Ignacio E. , Ast Gil , Kornblihtt Alberto R.
Published: June 2015

Alternative precursor messenger RNA (pre-mRNA) splicing plays a pivotal role in the flow of genetic information from DNA to proteins by expanding the coding capacity of genomes. Regulation of alternative splicing is as important as regulation of transcription to determine cell- and tissue-specific features, normal cell functioning, and responses of eukaryotic cells to external cues. Its importance is confirmed by the evolutionary conservation and diversification of alternative splicing and the fact that its deregulation causes hereditary disease and cancer. This review discusses the multiple layers of cotranscriptional regulation of alternative splicing in which chromatin structure, DNA methylation, histone marks, and nucleosome positioning play a fundamental role in providing a dynamic scaffold for interactions between the splicing and transcription machineries. We focus on evidence for how the kinetics of RNA polymerase II (RNAPII) elongation and the recruitment of splicing factors and adaptor proteins to chromatin components act in coordination to regulate alternative splicing.
Conservation Paleobiology: Leveraging Knowledge of the Past to Inform Conservation and Restoration
Authors: Dietl Gregory P. , Kidwell Susan M. , Brenner Mark , Burney David A. , Flessa Karl W. , Jackson Stephen T. , Koch Paul L.
Published: June 2015

Humans now play a major role in altering Earth and its biota. Finding ways to ameliorate human impacts on biodiversity and to sustain and restore the ecosystem services on which we depend is a grand scientific and societal challenge. Conservation paleobiology is an emerging discipline that uses geohistorical data to meet these challenges by developing and testing models of how biota respond to environmental stressors. Here we (a) describe how the discipline has already provided insights about biotic responses to key environmental stressors, (b) outline research aimed at disentangling the effects of multiple stressors, (c) provide examples of deliverables for managers and policy makers, and (d) identify methodological advances in geohistorical analysis that will foster the next major breakthroughs in conservation outcomes. We highlight cases for which exclusive reliance on observations of living biota may lead researchers to erroneous conclusions about the nature and magnitude of biotic change, vulnerability, and resilience.
Atmospheric Dynamics of Hot Exoplanets
Authors: Heng Kevin , Showman Adam P.
Published: June 2015

The characterization of exoplanetary atmospheres has come of age in the past decade, as astronomical techniques now allow for albedos, chemical abundances, temperature profiles and maps, rotation periods, and even wind speeds to be measured. Atmospheric dynamics sets the background state of density, temperature, and velocity that determines or influences the spectral and temporal appearance of an exoplanetary atmosphere. Hot exoplanets are most amenable to these characterization techniques. In this review, we focus on highly irradiated, large exoplanets (the hot Jupiters), as astronomical data begin to confront theoretical questions. We summarize the basic atmospheric quantities inferred from the astronomical observations. We review the state of the art by addressing a series of current questions, and look toward the future by considering a separate set of exploratory questions. Attaining the next level of understanding requires a concerted effort of constructing multifaceted, multiwavelength datasets for benchmark objects. Understanding clouds presents a formidable obstacle, as they introduce degeneracies into the interpretation of spectra, yet their properties and existence are directly influenced by atmospheric dynamics. Confronting general circulation models with these multifaceted, multiwavelength datasets will help us understand these and other degeneracies.
A Conversation with James J. Morgan
Authors: Morgan James J. , Newman Dianne K.
Published: June 2015

In conversation with professor Dianne Newman, Caltech geobiologist, James “Jim” J. Morgan recalls his early days in Ireland and New York City, education in parochial and public schools, and introduction to science in Cardinal Hayes High School, Bronx. In 1950, Jim entered Manhattan College, where he elected study of civil engineering, in particular water quality. Donald O'Connor motivated Jim's future study of O2 in rivers at Michigan, where in his MS work he learned to model O2 dynamics of rivers. As an engineering instructor at Illinois, Jim worked on rivers polluted by synthetic detergents. He chose to focus on chemical studies, seeing it as crucial for the environment. Jim enrolled for PhD studies with Werner Stumm at Harvard, who mentored his research in chemistry of particle coagulation and oxidation processes of Mn(II) and (IV). In succeeding decades, until retirement in 2000, Jim's teaching and research centered on aquatic chemistry; major themes comprised rates of abiotic manganese oxidation on particle surfaces and flocculation of natural water particles, and chemical speciation proved the key.
Exercise, cognitive function, and aging
Authors: Barnes Jill N.
Published: June 2015

Increasing the lifespan of a population is often a marker of a country's success. With the percentage of the population over 65 yr of age expanding, managing the health and independence of this population is an ongoing concern. Advancing age is associated with a decrease in cognitive function that ultimately affects quality of life. Understanding potential adverse effects of aging on brain blood flow and cognition may help to determine effective strategies to mitigate these effects on the population. Exercise may be one strategy to prevent or delay cognitive decline. This review describes how aging is associated with cardiovascular disease risks, vascular dysfunction, and increasing Alzheimer's disease pathology. It will also discuss the possible effects of aging on cerebral vascular physiology, cerebral perfusion, and brain atrophy rates. Clinically, these changes will present as reduced cognitive function, neurodegeneration, and the onset of dementia. Regular exercise has been shown to improve cognitive function, and we hypothesize that this occurs through beneficial adaptations in vascular physiology and improved neurovascular coupling. This review highlights the potential interactions and ideas of how the age-associated variables may affect cognition and may be moderated by regular exercise.
A faculty development program integrating cross-cultural care into a gastrointestinal pathophysiology tutorial benefits students, tutors, and the course
Authors: Shields Helen M. , Leffler Daniel A. , Peters Antoinette S. , Llerena-Quinn Roxana , Nambudiri Vinod E. , White Augustus A. , Hayward Jane N. , Pelletier Stephen R.
Published: June 2015

A specific faculty development program for tutors to teach cross-cultural care in a preclinical gastrointestinal pathophysiology course with weekly longitudinal followup sessions was designed in 2007 and conducted in the same manner over a 6-yr period. Anonymous student evaluations of how “frequently” the course and the tutor were actively teaching cross-cultural care were performed. The statements “This tutor actively teaches culturally competent care” and “Issues of culture and ethnicity were addressed” were significantly improved over baseline 2004 data. These increases were sustained over the 6-yr period. A tutor's overall rating as a teacher was moderately correlated with his/her “frequently” actively teaching cross-cultural care ( r = 0.385, P < 0. 001). Course evaluation scores were excellent and put the course into the group of preclinical courses with the top ratings. Students in the Race in Curriculum Group asked that the program be expanded to other preclinical courses. In conclusion, from 2007 to 2012, a faculty development program for teaching cross-cultural care consistently increased the discussion of cross-cultural care in the tutorial and course over each year beginning with 2007 compared with the baseline year of 2004. Our data suggest that cross-cultural care can be effectively integrated into pathophysiology tutorials and helps improve students' satisfaction and tutors' ratings. Teaching cross-cultural care in a pathophysiology tutorial did not detract from the course's overall evaluations, which remained in the top group over the 6-yr period.