BUDDHIST EQUILIBRIUM: THE THEORY OF MIDDLE PATH FOR SUSTAINABLE DEVELOPMENT

Environmental Economics and Policy,

CAPITALISM IN HUMAN SCALE: ARE THERE "VIRTUOUS CIRCLES" IN ECONOMIC GROWTH AND HUMAN DEVELOPMENT IN ACHIEVING A NEWLY INDUSTRIALIZED COUNTRY STATUS?

The purpose of this paper is two-fold: the first part is to understand the "virtuous circles" of economic growth and human development; the second part is to review the development literature related to this discussion. For this, the evolving development strategies of Sri Lanka and South Korea and the seemingly convergent two schools of thinking are briefly outlined in Section II. Section III surveys the pace of economic and human progress to give a broad background of the debate. Section IV analyzes the economic growth and human development in selected Industrialized Countries, Newly Industrialized Countries (NICs), Emerging NICs, and Aspiring South Asian neighbors of Sri Lanka...In the second part of the paper, a discussion of economic development literature and the experience of NICs are reviewed to learn from their policies and strategies in Section V.International Development,

THE POLITICAL ECONOMY OF POVERTY ALLEVIATION IN DEVELOPING COUNTRIES: IS SRI LANKA REALLY AN EXCEPTION?

Food Security and Poverty, Political Economy,

IMPACT OF GLOBALIZATION: THE INCIDENCE OF POVERTY AND FOOD SECURITY POLICIES IN SRI LANKA

Food Security and Poverty,

goSLP: Globally Optimized Superword Level Parallelism Framework

Modern microprocessors are equipped with single instruction multiple data (SIMD) or vector instruction sets which allow compilers to exploit superword level parallelism (SLP), a type of fine-grained parallelism. Current SLP auto-vectorization techniques use heuristics to discover vectorization opportunities in high-level language code. These heuristics are fragile, local and typically only present one vectorization strategy that is either accepted or rejected by a cost model. We present goSLP, a novel SLP auto-vectorization framework which solves the statement packing problem in a pairwise optimal manner. Using an integer linear programming (ILP) solver, goSLP searches the entire space of statement packing opportunities for a whole function at a time, while limiting total compilation time to a few minutes. Furthermore, goSLP optimally solves the vector permutation selection problem using dynamic programming. We implemented goSLP in the LLVM compiler infrastructure, achieving a geometric mean speedup of 7.58% on SPEC2017fp, 2.42% on SPEC2006fp and 4.07% on NAS benchmarks compared to LLVM's existing SLP auto-vectorizer.Comment: Published at OOPSLA 201

Response to the consultation ‘Regulating On-line Gambling in the EU: Recent Developments and Current Challenges from the Internal Market Standpoint'

This is a collaborative submission from a group of academics based in the UK with expertise in information technology law and related areas. The preparation of this response has been funded by the Information Technology Think Tank, which is supported by the Arts and Humanities Research Council and led by the SCRIPT/AHRC Centre for Research in Intellectual Property and Technology, University of Edinburgh. This response has been prepared by Abhilash Nair and Dinusha Mendis

The Application of Airtraq (fibreoptic intubation device) to Otolaryngology

The anaesthetic laryngoscope Airtraq is designed for the difficult airway. This disposable laryngoscope requires minimal cervical manipulation and unlike other common anaesthetic larynmgoscopes contains a channel for the guidance of an endotracheal tube. This could also be used for diagnosis and biopsy under a general anaesthetic or potentially under a local anaesthetic in an outpatient setting for biopsies or the removal of hypopharyngeal foreign bodies via flexible biopsy forceps obviating the need for a general anaesthetic. Thus Airtraq could be included in the armoury of pre-existing direct laryngoscopes because of its virtue of minimal airway manipulation

On the origin of comets

Physico-chemical processes leading to the dynamic formation and physical evolution of comets are reviewed in relationship to the various theories that propose solar origins, protoplanetary origins, planetary origins and interstellar origins. Evidence points to the origins of comets by the growth and agglomeration of small particles from gas and dust at very low temperatures at undetermined regions in space

Spectral Attention-Driven Intelligent Target Signal Identification on a Wideband Spectrum

This paper presents a spectral attention-driven reinforcement learning based intelligent method for effective and efficient detection of important signals in a wideband spectrum. In the work presented in this paper, it is assumed that the modulation technique used is available as a priori knowledge of the targeted important signal. The proposed spectral attention-driven intelligent method is consists of two main components, a spectral correlation function (SCF) based spectral visualization scheme and a spectral attention-driven reinforcement learning mechanism that adaptively selects the spectrum range and implements the intelligent signal detection. Simulations illustrate that the proposed method can achieve high accuracy of signal detection while observation of spectrum is limited to few ranges via effectively selecting the spectrum ranges to be observed. Furthermore, the proposed spectral attention-driven machine learning method can lead to an efficient adaptive intelligent spectrum sensor designs in cognitive radio (CR) receivers.Comment: 6 pages, 11 figure

Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks

Predicting the number of clock cycles a processor takes to execute a block of assembly instructions in steady state (the throughput) is important for both compiler designers and performance engineers. Building an analytical model to do so is especially complicated in modern x86-64 Complex Instruction Set Computer (CISC) machines with sophisticated processor microarchitectures in that it is tedious, error prone, and must be performed from scratch for each processor generation. In this paper we present Ithemal, the first tool which learns to predict the throughput of a set of instructions. Ithemal uses a hierarchical LSTM--based approach to predict throughput based on the opcodes and operands of instructions in a basic block. We show that Ithemal is more accurate than state-of-the-art hand-written tools currently used in compiler backends and static machine code analyzers. In particular, our model has less than half the error of state-of-the-art analytical models (LLVM's llvm-mca and Intel's IACA). Ithemal is also able to predict these throughput values just as fast as the aforementioned tools, and is easily ported across a variety of processor microarchitectures with minimal developer effort.Comment: Published at 36th International Conference on Machine Learning (ICML) 201