bluuebunny/crossref_metadata_2025_split huggingface dataset:
Automatic compilation of MATLAB programs for synergistic execution on heterogeneous processors
Authors: Prasad Ashwin , Anantpur Jayvant , Govindarajan R. 
Published: October 2012

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance.
In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.
Safe optimisations for shared-memory concurrent programs
Authors: Ševčík Jaroslav 
Published: October 2012

Current proposals for concurrent shared-memory languages, including C++ and C, provide sequential consistency only for programs without data races (the DRF guarantee). While the implications of such a contract for hardware optimisations are relatively well-understood, the correctness of compiler optimisations under the DRF guarantee is less clear, and experience with Java shows that this area is error-prone.
In this paper we give a rigorous study of optimisations that involve both reordering and elimination of memory reads and writes, covering many practically important optimisations. We first define powerful classes of transformations semantically, in a language-independent trace semantics. We prove that any composition of these transformations is sound with respect to the DRF guarantee, and moreover that they provide basic security guarantees (no thin-air reads) even for programs with data races. To give a concrete example, we apply our semantic results to a simple imperative language and prove that several syntactic transformations are safe for that language. We also discuss some surprising limitations of the DRF guarantee.
Automated atomicity-violation fixing
Authors: Jin Guoliang , Song Linhai , Zhang Wei , Lu Shan , Liblit Ben 
Published: October 2012

Fixing software bugs has always been an important and time-consuming process in software development. Fixing concurrency bugs has become especially critical in the multicore era. However, fixing concurrency bugs is challenging, in part due to non-deterministic failures and tricky parallel reasoning. Beyond correctly fixing the original problem in the software, a good patch should also avoid introducing new bugs, degrading performance unnecessarily, or damaging software readability. Existing tools cannot automate the whole fixing process and provide good-quality patches.
We present AFix, a tool that automates the whole process of fixing one common type of concurrency bug: single-variable atomicity violations. AFix starts from the bug reports of existing bug-detection tools. It augments these with static analysis to construct a suitable patch for each bug report. It further tries to combine the patches of multiple bugs for better performance and code readability. Finally, AFix's run-time component provides testing customized for each patch. Our evaluation shows that patches automatically generated by AFix correctly eliminate six out of eight real-world bugs and significantly decrease the failure probability in the other two cases. AFix patches never introduce new bugs and usually have similar performance to manually-designed patches.
NDSeq
Authors: Burnim Jacob , Elmas Tayfun , Necula George , Sen Koushik 
Published: October 2012

We propose to specify the correctness of a program's parallelism using a sequential version of the program with controlled nondeterminism. Such a
nondeterministic sequential specification
allows (1) the correctness of parallel interference to be verified independently of the program's functional correctness, and (2) the functional correctness of a program to be understood and verified on a sequential version of the program, one with controlled nondeterminism but no interleaving of parallel threads.

We identify a number of common patterns for writing nondeterministic sequential specifications. We apply these patterns to specify the parallelism correctness for a variety of parallel Java benchmarks, even in cases when the functional correctness is far too complex to feasibly specify.
We describe a sound runtime checking technique to validate that an execution of a parallel program conforms to its nondeterministic sequential specification. The technique uses a novel form of conflict-serializability checking to identify, for a given interleaved execution of a parallel program, an equivalent nondeterministic sequential execution. Our experiments show a significant reduction in the number of false positives versus traditional conflict-serializability in checking for parallelization bugs.
Exploiting the commutativity lattice
Authors: Kulkarni Milind , Nguyen Donald , Prountzos Dimitrios , Sui Xin , Pingali Keshav 
Published: October 2012

Speculative execution is a promising approach for exploiting parallelism in many programs, but it requires efficient schemes for detecting conflicts between concurrently executing threads. Prior work has argued that checking semantic commutativity of method invocations is the right way to detect conflicts for complex data structures such as kd-trees. Several ad hoc ways of checking commutativity have been proposed in the literature, but there is no systematic approach for producing implementations.
In this paper, we describe a novel framework for reasoning about commutativity conditions: the commutativity lattice. We show how commutativity specifications from this lattice can be systematically implemented in one of three different schemes: abstract locking, forward gatekeeping and general gatekeeping. We also discuss a disciplined approach to exploiting the lattice to find different implementations that trade off precision in conflict detection for performance. Finally, we show that our novel conflict detection schemes are practical and can deliver speedup on three real-world applications.
On inter-procedural analysis of programs with lists and data
Authors: Bouajjani Ahmed , Drăgoi Cezara , Enea Constantin , Sighireanu Mihaela 
Published: October 2012

We address the problem of automatic synthesis of assertions on sequential programs with singly-linked lists containing data over infinite domains such as integers or reals. Our approach is based on an accurate abstract inter-procedural analysis. Program configurations are represented by graphs where nodes represent list segments without sharing. The data in these list segments are characterized by constraints in abstract domains. We consider a domain where constraints are in a universally quantified fragment of the first-order logic over sequences, as well as a domain constraining the multisets of data in sequences.
Our analysis computes the effect of each procedure in a local manner, by considering only the reachable part of the heap from its actual parameters. In order to avoid losses of information, we introduce a mechanism based on unfolding/folding operations allowing to strengthen the analysis in the domain of first-order formulas by the analysis in the multisets domain.
The same mechanism is used for strengthening the sound (but incomplete) entailment operator of the domain of first-order formulas. We have implemented our techniques in a prototype tool and we have shown that our approach is powerful enough for automatic (1) generation of non-trivial procedure summaries, (2) pre/post-condition reasoning, and (3) procedure equivalence checking.
Taming the wildcards
Authors: Altidor John , Huang Shan Shan , Smaragdakis Yannis 
Published: October 2012

Variance allows the safe integration of parametric and subtype polymorphism. Two flavors of variance, definition-site versus use-site variance, have been studied and have had their merits hotly debated. Definition-site variance (as in Scala and C#) offers simple type-instantiation rules, but causes fractured definitions of naturally invariant classes; Use-site variance (as in Java) offers simplicity in class definitions, yet complex type-instantiation rules that elude most programmers.
We present a unifying framework for reasoning about variance. Our framework is quite simple and entirely denotational, that is, it evokes directly the definition of variance with a small core calculus that does not depend on specific type systems. This general framework can have multiple applications to combine the best of both worlds: for instance, it can be used to add use-site variance annotations to the Scala type system. We show one such application in detail: we extend the Java type system with a mechanism that modularly infers the definition-site variance of type parameters, while allowing use-site variance annotations on any type-instantiation.
Applying our technique to six Java generic libraries (including the Java core library) shows that 20-58 (depending on the library) of generic definitions are inferred to have single-variance; 8-63% of method signatures can be relaxed through this inference, and up to 91% of existing wildcard annotations are unnecessary and can be elided.
Targeting Cancer Metabolism
Authors: Teicher Beverly A. , Linehan W. Marston , Helman Lee J. 
Published: October 2012

Abstract
The understanding that oncogenes can have profound effects on cellular metabolism and the discovery of mutations and alterations in several metabolism-related enzymes—isocitrate dehydrogenase 1 (IDH1), isocitrate dehydrogenase 2 (IDH2), succinate dehydrogenase (SDH), fumarate hydratase (FH), and pyruvate kinase M2 (PKM2)—has renewed interest in cancer metabolism and renewed hope of taking therapeutic advantage of cancer metabolism. Otto Warburg observed that aerobic glycolysis was a characteristic of cancer cells. More than 50 years later, we understand that aerobic glycolysis and uptake of glutamine and glycine allow cancer cells to produce energy (ATP) and the nucleotides, amino acids, and lipids required for proliferation. Expression of the MYC oncogene drives the increase in cellular biomass facilitating proliferation. PKM2 expression in cancer cells stimulates aerobic glycolysis. Among intermediary metabolism enzymes, mutations in SDH occur in gastointestinal stromal tumors and result in a pseudohypoxic metabolic milieu. FH mutations lead to a characteristic renal cell carcinoma. Isocitrate dehydrogenase (IDH1/2) mutations have been found in leukemias, gliomas, prostate cancer, colon cancer, thyroid cancer, and sarcomas. These recently recognized oncogenic metabolic lesions may be selective targets for new anticancer therapeutics. Clin Cancer Res; 18(20); 5537–45. ©2012 AACR.
Resiliency of Lung Cancers to EGFR Inhibitor Treatment Unveiled, Offering Opportunities to Divide and Conquer EGFR Inhibitor Resistance
Authors: Blakely Collin M. , Bivona Trever G. 
Published: October 2012

Abstract
Summary: The clinical success of EGF receptor (EGFR) inhibitors in patients with lung cancer is limited by the inevitable development of treatment resistance. Two reports in this issue of Cancer Discovery uncover additional mechanisms by which EGFR-mutant lung cancers escape from EGFR kinase inhibitor treatment. These findings pave the way for clinical testing of new rational therapeutic strategies to prevent or overcome resistance to EGFR kinase inhibitors in the clinic. Cancer Discov; 2(10); 872–5. ©2012 AACR.
Commentary on Ercan et al., p. 934.
Commentary on Takezawa et al., p. 922.
Histology, Anatomy, or Geography? Exome Sequencing Begins to Delineate Somatic Mutational Differences in Esophageal Cancer
Authors: Collisson Eric A. , Cho Raymond J. 
Published: October 2012

Abstract
Summary: Esophageal carcinoma is composed of squamous cell and adenocarcinoma types, each with geographically distinct incidence. The earliest exome sequences in this disease begin to illuminate the genetic demarcations of these anatomically related cancers. Cancer Discov; 2(10); 870–1. ©2012 AACR.
Commentary on Agrawal et al., p. 899.
Compensatory Pathways in Oncogenic Kinase Signaling and Resistance to Targeted Therapies: Six Degrees of Separation
Authors: Trusolino Livio , Bertotti Andrea 
Published: October 2012

Abstract
Summary: The efficacy of targeted therapies against mutationally activated kinases is typically limited by the engagement of growth-promoting cues that compensate for inhibition of the targeted kinase. Initial studies have highlighted the contribution of genomic alterations, functional characteristics, and signaling feedback loops—all intrinsic to cancer cells—in sustaining such substitute activities. New evidence now indicates that the relative expression of growth factor ligands produced by the tumor microenvironment can relay redundant survival pathways, which may broadly impair responsiveness to kinase inhibitors. Cancer Discov; 2(10); 876–80. ©2012 AACR.
Amygdala Sensitivity to Race Is Not Present in Childhood but Emerges over Adolescence
Authors: Telzer Eva H. , Humphreys Kathryn L. , Shapiro Mor , Tottenham Nim 
Published: October 2012

Abstract
Neuroimaging research in adults has consistently found that differential perception of race is associated with increased amygdala activity. We hypothesized that such neural biases unlikely reflect innate processes but instead emerge over development. In the current study, we used fMRI to examine the neurodevelopmental trajectory of the amygdala in response to race across childhood and adolescence ranging from 4 to 16 years. Thirty-two youths viewed African American and European American faces during a functional brain scan. Results suggest that differential amygdala response to African American faces does not emerge until adolescence, reflecting the increasing salience of race across development. In addition, greater peer diversity was associated with attenuated amygdala response to African American faces, suggesting that intergroup racial contact may reduce the salience of race.
A Study of the North Atlantic Oscillation Using Conditional Nonlinear Optimal Perturbation
Authors: Jiang Zhina , Mu Mu , Luo Dehai 
Published: October 2012

AbstractThe conditional nonlinear optimal perturbation (CNOP) method is used to explore the optimal precursors that trigger the North Atlantic Oscillation (NAO) anomaly pattern with a triangular T21, three-level, quasi-geostrophic global spectral model based on a viewpoint that the NAO is a nonlinear initial-value problem. With a three-dimensional winter climatological flow as the basic state, initially baroclinic localized optimal precursors on the northward flanks of the climatological Atlantic jet undergo wave breaking during their evolution into the NAO-like anomalies. Accompanied with the formation of the NAO, the north–south variability of the zonal mean westerly anomaly has arisen.Analysis reveals that in the evolution of optimal precursors, the role played by the self-interaction of perturbations (viz., the nonlinear process) in the onset of the negative-phase NAO (NAO−) event is stronger than that in the onset of the positive-phase NAO (NAO+) event. Both the perturbation/basic-state interaction and self-interaction of perturbations determine whether the NAO− event occurs, whereas the nonlinearity process in the NAO+ onset only appears to modulate the structure of the perturbation to have a dipole mode over the North Atlantic at the optimization time, and meanwhile cause this dipole mode to become zonally extended. That is to say, the nonlinear process indeed plays an important role during the onset of an NAO event and the CNOP method is a useful tool to identify the dynamics of the onset of NAO teleconnection patterns.
Deducing Multidecadal Anthropogenic Global Warming Trends Using Multiple Regression Analysis
Authors: Zhou Jiansong , Tung Ka-Kit 
Published: October 2012

Abstract
To unmask the anthropogenic global warming trend imbedded in the climate data, multiple linear regression analysis is often employed to filter out short-term fluctuations caused by El Niño–Southern Oscillation (ENSO), volcano aerosols, and solar forcing. These fluctuations are unimportant as far as their impact on the deduced multidecadal anthropogenic trends is concerned: ENSO and volcano aerosols have very little multidecadal trend. Solar variations do have a secular trend, but it is very small and uncertain. What is important, but is left out of all multiple regression analysis of global warming so far, is a long-period oscillation called the Atlantic multidecadal oscillation (AMO). When the AMO index is included as a regressor (i.e., explanatory variable), the deduced multidecadal anthropogenic global warming trend is so impacted that previously deduced anthropogenic warming rates need to be substantially revised. The deduced net anthropogenic global warming trend has been remarkably steady and statistically significant for the past 100 yr.
Extracting Subseasonal Scenarios: An Alternative Method to Analyze Seasonal Predictability of Regional-Scale Tropical Rainfall
Authors: Moron Vincent , Camberlin Pierre , Robertson Andrew W. 
Published: October 2012

Abstract
Current seasonal prediction of rainfall typically focuses on 3-month rainfall totals at regional scale. This temporal summation reduces the noise related to smaller-scale weather variability but also implicitly emphasizes the peak of the climatological seasonal cycle of rainfall. This approach may hide potentially predictable signals when rainfall is lower: for example, near the onset or cessation of the rainy season. The authors illustrate such a case for the East African long rains (March–May) on a network of 36 stations in Kenya and north Tanzania from 1961 to 2001. Spatial coherence and potential predictability of seasonal rainfall anomalies associated with tropical sea surface temperature (SST) anomalies clearly peak during the early stage of the rainy season (in March), while the largest rainfall (in April and May) is far less spatially coherent; the latter is shown to contain a large noise component at the station scale that characterizes interannual variability of the March–May seasonal total amounts. Combining the empirical orthogonal function of both interannual and subseasonal variations with a fuzzy k-means clustering is shown to capture the most spatially coherent subseasonal “scenarios” that tend to filter out the noisier variations of the rainfall field and emphasize the most consistent signals in both time and space. This approach is shown to provide insight into the seasonal predictability of long dry spells and heavy daily rainfall events at local scale and their subseasonal modulation.
Multiscale Evaluation of the Improvements in Surface Snow Simulation through Terrain Adjustments to Radiation
Authors: Kumar Sujay V. , Peters-Lidard Christa D. , Mocko David , Tian Yudong 
Published: October 2012

Abstract
The downwelling shortwave radiation on the earth’s land surface is affected by the terrain characteristics of slope and aspect. These adjustments, in turn, impact the evolution of snow over such terrain. This article presents a multiscale evaluation of the impact of terrain-based adjustments to incident shortwave radiation on snow simulations over two midlatitude regions using two versions of the Noah land surface model (LSM). The evaluation is performed by comparing the snow cover simulations against the 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover product. The model simulations are evaluated using categorical measures, such as the probability of detection of “yes” events (PODy), which measure the fraction of snow cover presence that was correctly simulated, and false alarm ratio (FAR), which measures the fraction of no-snow events that was incorrectly simulated. The results indicate that the terrain-based correction of radiation leads to systematic improvements in the snow cover estimates in both domains and in both LSM versions (with roughly 12% overall improvement in PODy and 5% improvement in FAR), with larger improvements observed during snow accumulation and melt periods. Increased contribution to PODy and FAR improvements is observed over the north- and south-facing slopes, when the overall improvements are stratified to the four cardinal aspect categories. A two-dimensional discrete Haar wavelet analysis for the two study areas indicates that the PODy improvements in snow cover estimation drop to below 10% at scales coarser than 16 km, whereas the FAR improvements are below 10% at scales coarser than 4 km.
Implementation of Real-Time Quality Control Procedures by Means of a Probabilistic Estimate of Seawater Temperature and Its Temporal Evolution
Authors: Manzella Giuseppe M. R. , Gambetta Marco 
Published: October 2012

Abstract
Near-real-time quality control procedures for temperature profiles collected from ships of opportunity were implemented during the 1980s in oceans across the world and from the 1990s in the Mediterranean. In this sea, the procedures were originally based on seven steps (detection of end of profile, gross range check, position control, elimination of spikes, Gaussian smoothing and resampling at 1-m intervals, general malfunction control, and comparison with climatology), complemented with initial and final visual checks. The quality of data derived from a comparison with historical data (namely, climatology) depends on the availability of a huge amount of data that can statistically represent the mean characteristics of the seawater. A significant amount of data has been collected, and the existing temperature database in the Mediterranean can now provide more information on temporal and spatial variability at monthly and mesoscales, and an improved procedure for data quality control has now been adopted. New “best” estimates of monthly temperature profiles are calculated by using a maximum likelihood method. It has been found that more than one “best estimate” temperature can be defined in particular areas and depths, as a consequence of climate variability. Additional near-real-time control procedures have been included in order to provide information on long-term variability associated with data. This information is included in metafiles to be used for reanalysis and studies on long-term variability and changes.