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

Economic Effects on Million Dollar Giving

This study investigates the impact of economic factors on the number of charitable gifts of one million dollars or more within the United States using the Million Dollar List dataset. We investigate key donor groups: individuals, corporations, and foundations. Results indicate that individual donors are particularly responsive to underlying economic conditions; giving by foundations tends to be counter-cyclical, and corporate giving is not significantly associated with macroeconomic factors. We also find that economic conditions vary in their influence on giving to subsectors, and gifts to public benefit and human services organizations increase significantly during periods of recession. Findings from our study have direct implications for philanthropists, fundraisers, and policy makes as they seek to understand how economic conditions impact large gifts

Lyapunov-type inequalities for quasilinear systems with antiperiodic boundary conditions

We establish some new Lyapunov-type inequalities for one-dimensional p-Laplacian systems with antiperiodic boundary conditions. The lower bounds of eigenvalues are presented.Встановлено дєякі нові нєрівності типу Ляпунова для одновимірних p-лапласових систем з антиперіодичними граничними умовами. Наведено нижні межі для власних значень

Lyapunov-type inequalities for (m+1)(m+1)th order half-linear differential equations with anti-periodic boundary conditions

In this work, we will establish several new Lyapunov-type inequalities for $(m+1)$th order half-linear differential equations with anti-periodic boundary conditions, the results of this paper are new and generalize and improve some early results in the literature