A 2 epoch proper motion catalogue from the UKIDSS Large Area Survey

This is an Open Access article distributed under the terms of the Creative Commons Attribution License 2.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedThe UKIDSS Large Area Survey (LAS) began in 2005, with the start of the UKIDSS program as a 7 year effort to survey roughly 4000 square degrees at high galactic latitudes in Y, J, H and K bands. The survey also included a significant quantity of 2-epoch J band observations, with epoch baselines ranging from 2 to 7 years. We present a proper motion catalogue for the 1500 square degrees of the 2 epoch LAS data, which includes some 800,000 sources with motions detected above the 5 sigma level. We developed a bespoke proper motion pipeline which applies a source-unique second order polynomial transformation to UKIDSS array coordinates of each source to counter potential local non-uniformity in the focal plane. Our catalogue agrees well with the proper motion data supplied in the current WFCAM Science Archive (WSA) DR9 catalogue where there is overlap, and in various optical catalogues, but it benefits from some improvements. One improvement is that we provide absolute proper motions, using LAS galaxies for the relative to absolute correction. Also, by using unique, local, 2nd order polynomial tranformations, as opposed to the linear transformations in the WSA, we correct better for any local distortions in the focal plane, not including the radial distortion that is removed by their pipeline

Learning to Accelerate Symbolic Execution via Code Transformation

Symbolic execution is an effective but expensive technique for automated test generation. Over the years, a large number of refined symbolic execution techniques have been proposed to improve its efficiency. However, the symbolic execution efficiency problem remains, and largely limits the application of symbolic execution in practice. Orthogonal to refined symbolic execution, in this paper we propose to accelerate symbolic execution through semantic-preserving code transformation on the target programs. During the initial stage of this direction, we adopt a particular code transformation, compiler optimization, which is initially proposed to accelerate program concrete execution by transforming the source program into another semantic-preserving target program with increased efficiency (e.g., faster or smaller). However, compiler optimizations are mostly designed to accelerate program concrete execution rather than symbolic execution. Recent work also reported that unified settings on compiler optimizations that can accelerate symbolic execution for any program do not exist at all. Therefore, in this work we propose a machine-learning based approach to tuning compiler optimizations to accelerate symbolic execution, whose results may also aid further design of specific code transformations for symbolic execution. In particular, the proposed approach LEO separates source-code functions and libraries through our program-splitter, and predicts individual compiler optimization (i.e., whether a type of code transformation is chosen) separately through analyzing the performance of existing symbolic execution. Finally, LEO applies symbolic execution on the code transformed by compiler optimization (through our local-optimizer). We conduct an empirical study on GNU Coreutils programs using the KLEE symbolic execution engine. The results show that LEO significantly accelerates symbolic execution, outperforming the default KLEE configurations (i.e., turning on/off all compiler optimizations) in various settings, e.g., with the default training/testing time, LEO achieves the highest line coverage in 50/68 programs, and its average improvement rate on all programs is 46.48%/88.92% in terms of line coverage compared with turning on/off all compiler optimizations

Automatic MPI to AMPI Program Transformation Using Photran

Abstract. Adaptive MPI, or AMPI, is an implementation of the Mes-sage Passing Interface (MPI) standard. AMPI benefits MPI applications with features such as dynamic load balancing, virtualization, and check-pointing. Because AMPI uses multiple user-level threads per physical core, global variables become an obstacle. It is thus necessary to con-vert MPI programs to AMPI by eliminating global variables. Manually removing the global variables in the program is tedious and error-prone. In this paper, we present a Photran-based tool that automates this task with a source-to-source transformation that supports Fortran. We eval-uate our tool on the multi-zone NAS Benchmarks with AMPI. We also demonstrate the tool on a real-world large-scale FLASH code and present preliminary results of running FLASH on AMPI. Both results show sig-nificant performance improvement using AMPI. This demonstrates that the tool makes using AMPI easier and more productive.

Constraint Based Compiler Optimization for Energy Harvesting Applications

We propose a method for optimizing the energy efficiency of software code running on small computing devices in the Internet of Things (IoT) that are powered exclusively by electricity harvested from ambient energy in the environment. Due to the weak and unstable nature of the energy source, it is challenging for developers to manually optimize the software code to deal with mismatch between the intermittent power supply and the computation demand. Our method overcomes the challenge by using a combination of three techniques. First, we use static program analysis to automatically identify opportunities for precomputation, i.e., computation that may be performed ahead of time as opposed to just in time. Second, we optimize the precomputation policy, i.e., a way to split and reorder steps of a computation task in the original software to match the intermittent power supply while satisfying a variety of system requirements; this is accomplished by formulating energy optimization as a constraint satisfiability problem and then solving the problem using an off-the-shelf SMT solver. Third, we use a state-of-the-art compiler platform (LLVM) to automate the program transformation to ensure that the optimized software code is correct by construction. We have evaluated our method on a large number of benchmark programs, which are C programs implementing secure communication protocols that are popular for energy-harvesting IoT devices. Our experimental results show that the method is efficient in optimizing all benchmark programs. Furthermore, the optimized programs significantly outperform the original programs in terms of energy efficiency and latency, and the overall improvement ranges from 2.3X to 36.7X

Darwinian Data Structure Selection

Data structure selection and tuning is laborious but can vastly improve an application's performance and memory footprint. Some data structures share a common interface and enjoy multiple implementations. We call them Darwinian Data Structures (DDS), since we can subject their implementations to survival of the fittest. We introduce ARTEMIS a multi-objective, cloud-based search-based optimisation framework that automatically finds optimal, tuned DDS modulo a test suite, then changes an application to use that DDS. ARTEMIS achieves substantial performance improvements for \emph{every} project in $5$ Java projects from DaCapo benchmark, $8$ popular projects and $30$ uniformly sampled projects from GitHub. For execution time, CPU usage, and memory consumption, ARTEMIS finds at least one solution that improves \emph{all} measures for $86\%$ ($37/43$) of the projects. The median improvement across the best solutions is $4.8\%$, $10.1\%$, $5.1\%$ for runtime, memory and CPU usage. These aggregate results understate ARTEMIS's potential impact. Some of the benchmarks it improves are libraries or utility functions. Two examples are gson, a ubiquitous Java serialization framework, and xalan, Apache's XML transformation tool. ARTEMIS improves gson by $16.5$\%, $1\%$ and $2.2\%$ for memory, runtime, and CPU; ARTEMIS improves xalan's memory consumption by $23.5$\%. \emph{Every} client of these projects will benefit from these performance improvements.Comment: 11 page

AutoAccel: Automated Accelerator Generation and Optimization with Composable, Parallel and Pipeline Architecture

CPU-FPGA heterogeneous architectures are attracting ever-increasing attention in an attempt to advance computational capabilities and energy efficiency in today's datacenters. These architectures provide programmers with the ability to reprogram the FPGAs for flexible acceleration of many workloads. Nonetheless, this advantage is often overshadowed by the poor programmability of FPGAs whose programming is conventionally a RTL design practice. Although recent advances in high-level synthesis (HLS) significantly improve the FPGA programmability, it still leaves programmers facing the challenge of identifying the optimal design configuration in a tremendous design space. This paper aims to address this challenge and pave the path from software programs towards high-quality FPGA accelerators. Specifically, we first propose the composable, parallel and pipeline (CPP) microarchitecture as a template of accelerator designs. Such a well-defined template is able to support efficient accelerator designs for a broad class of computation kernels, and more importantly, drastically reduce the design space. Also, we introduce an analytical model to capture the performance and resource trade-offs among different design configurations of the CPP microarchitecture, which lays the foundation for fast design space exploration. On top of the CPP microarchitecture and its analytical model, we develop the AutoAccel framework to make the entire accelerator generation automated. AutoAccel accepts a software program as an input and performs a series of code transformations based on the result of the analytical-model-based design space exploration to construct the desired CPP microarchitecture. Our experiments show that the AutoAccel-generated accelerators outperform their corresponding software implementations by an average of 72x for a broad class of computation kernels

Affective Sustainability. The Creation and Transmission of Affect through an Educative Process: An Instrument for the Construction of more Sustainable Citizens

Although for many years the debate on sustainability has focused on the generation of critical thinking based on the dynamic balance between the economic, social and environmental spheres, in the following text we propose to elaborate on the use of a eminently human condition, such as the capacity to love and create an emotional attachment, whether with our environment or our fellow men, as an initiator and main force for change to the building a more sustainable model of development. To do so we shall begin from the concept coined by Adriana Bisquert in the 90s, that is A ective sustainability, by analyzing it, delving into its possible definitions by means of the development of the project for Environmental Education and Development called “Educating for a more sustainable citizenship” undertaken by the Spanish NGO (non-governmental organization) or ITACA Ambiente Elegido, and developed in the locality of Paterna de Rivera, Cádiz (Spain). This is a practical and real example, which is used to establish a work educational methodology that enables us to consider this concept as the real basis for an exportable and replicable work in a painstaking search for the creation of a more sustainable city

Iowa Department of Corrections Annual Performance Report, FY2006

Agency Performance Repor

Isolasi gen palmitoyl-acpthioesterase pada kelapa sawit (Elaies guineensis Jacq.)=Isolation ofPalmitoyl-ACP Thioesterase Gene on OilPalm (Elaies guineensis Jacq.)

ABSTRACT Plant quality improvement, as a source of oil, was one of the objective of oil palm plant breeding program, such as genetic engineering. Palmitoyl-ACP thioesterase (PAT) gene was an enzyme code, which influenced the synthesis of palmitic acid, where its existence was unexpected in crude palm oil (CPO), due to its negative impact on human health. The first step in genetic engineering was isolating the gene which related to the plant\u27s negative trait. The gene silencing phase was expected to avoid the expression of gene PAT, to reduce the proportion of palmitic acid as well as increasing the content of oleic acid, which was expected to present in CPO. The aim of the research was to identify nucleoride sequence of the PAT gene of the oil palm. The procedure of the research included, extraction the DNA from leaves, gene isolation through specific primer design and amplification, cloning the PAT gene including ligation and transformation, a series of confirmation and verification, and PAT gene sequencing. The result showed that 2 fragments of DN A had been isolated by using 2 different pair of primers, they was PAT I and PAT II fragment. PAT I gene fragment was amplified by using PAT II and PAT TF primers. Recombinant plasmid carrying PAT I gene fragment had been produced through cloning, ligation and transformation inside the strain of DH5a Escherichia coli. The targeted fragment inside the plasmid then was sequence and producing 1,063 bp fragment. 750 bp length PAT II gene, was amplified by PAT U and PAT UR primer. Keywords: Palmitoyl-ACP thioesterase gene, Elaeis guineensis Jacq., isolation cloning, and sequencing