The splicing of backscattered scanning electron microscopy method used on evaluation of microscopic pore characteristics in shale sample and compared with results from other methods

The splicing of backscattered scanning electron microscopy (SB-SEM) method was applied to evaluate the microscopic pore characteristics of the Lower Silurian Longmaxi Shale samples from Py1 well in Southeast Chongqing, China. The results from SB-SEM, including frequencies, volumes and specific surface areas of organic and inorganic pores with different sizes, were compared with those of low temperature nitrogen adsorption/desorption (LTNA) and mercury intrusion porosimetry (MIP). The results show that the changes in organic and inorganic surface porosity with increasing image area estimated from the SB-SEM method become almost stable when the SB-SEM image areas are larger than 0.4 mm, which indicates that the heterogeneities of organic and inorganic pore volumes in shale samples can be largely overcome. This method is suitable for evaluating the microscopic pore characteristics of shale samples. Although the SB-SEM underestimates the frequencies, volumes and specific surface areas of pores smaller than its resolution, it can obtain these characteristics of pores larger than 100 nm in width, which are not effectively evaluated by the LTNA method and are underestimated by the MIP method

Call Sequence Prediction through Probabilistic Calling Automata

Predicting a sequence of upcoming function calls is important for optimizing programs written in modern managed languages (e.g., Java, Javascript, C#.) Existing function call predictions are mainly built on statistical patterns, suitable for predicting a single call but not a sequence of calls. This paper presents a new way to enable call sequence prediction, which exploits program structures through Probabilistic Calling Automata (PCA), a new program representation that captures both the inherent ensuing relations among function calls, and the probabilistic nature of execution paths. It shows that PCA-based prediction outperforms existing predictions, yielding substantial speedup when being applied to guide Just-In-Time compilation. By enabling accurate, efficient call sequence prediction for the first time, PCA-based predictors open up many new opportunities for dynamic program optimizations

A key-based adaptive transactional memory executor

Software transactional memory systems enable a programmer to easily write concurrent data structures such as lists, trees, hashtables, and graphs, where nonconflicting operations proceed in parallel. Many of these structures take the abstract form of a dictionary, in which each transaction is associated with a search key. By regrouping transactions based on their keys, one may improve locality and reduce conflicts among parallel transactions. In this paper, we present an executor that partitions transactions among available processors. Our keybased adaptive partitioning monitors incoming transactions, estimates the probability distribution of their keys, and adaptively determines the (usually nonuniform) partitions. By comparing the adaptive partitioning with uniform partitioning and round-robin keyless partitioning on a 16-processor SunFire 6800 machine, we demonstrate that key-based adaptive partitioning significantly improves the throughput of finegrained parallel operations on concurrent data structures

Insight into Differential Responses of Upland and Paddy Rice to Drought Stress by Comparative Expression Profiling Analysis

In this study, the drought responses of two genotypes, IRAT109 and Zhenshan 97 (ZS97), representing upland and paddy rice, respectively, were systematically compared at the morphological, physiological and transcriptional levels. IRAT109 has better performance in traits related to drought avoidance, such as leaf rolling, root volumes, the ratio of leaf water loss and relative conductivity. At the transcriptional level, more genes were induced by drought in IRAT109 at the early drought stage, but more genes had dynamic expression patterns in ZS97 at different drought degrees. Under drought conditions, more genes related to reproductive development and establishment of localization were repressed in IRAT109, but more genes involved in degradation of cellular components were induced in ZS97. By checking the expression patterns of 36 drought-responsive genes (located in 14 quantitative trail loci [QTL] intervals) in ZS97, IRAT109 and near isogenic lines (NILs) of the QTL intervals, we found that more than half of these genes had their expression patterns or expression levels changed in the NILs when compared to that in ZS97 or IRAT109. Our results may provide valuable information for dissecting the genetic bases of traits related to drought resistance, as well as for narrowing the candidate genes for the traits

Parallelization of utility programs based on behavior phase analysis

Abstract. With the fast development of multi-core processors, automatic parallelization becomes increasingly important. In this work, we focus on the parallelization of utility programs, a class of commonly used applications including compilers, transcoding utilities, file compressions, and databases. They take a series of requests as inputs and serve them one by one. Their high input dependence poses a challenge to parallelization. We use active profiling to find behavior phase boundaries and then automatically detect run-time dependences through profiling. Using a unified framework, we manually parallelize programs at phase boundaries. We show that for two programs, the technique enables parallelization at large granularity, which may span many loops and subroutines. The parallelized programs show significant speedup on multi-processor machines.