Abstract:The present paper is devoted to a theoretical analysis of sliding friction under the influence of oscillations perpendicular to the sliding plane. In contrast to previous works we analyze the influence of the stiffness of the tribological contact in detail and also consider the case of large oscillation amplitudes at which the contact is lost during a part of the oscillation period, so that the sample starts to "jump". It is shown that the macroscopic coefficient of friction is a function of only two dimensionless parameters-a dimensionless sliding velocity and dimensionless oscillation amplitude. This function in turn depends on the shape of the contacting bodies. In the present paper, analysis is carried out for two shapes: a flat cylindrical punch and a parabolic shape. Here we consider "stiff systems", where the contact stiffness is small compared with the stiffness of the system. The role of the system stiffness will be studied in more detail in a separate paper.

Agent-based simulations are becoming widespread among scientists from different areas, who use them to model increasingly complex problems. To cope with the growing computational complexity, parallel and distributed implementations have been developed for a wide range of platforms. However, it is difficult to have simulations that are portable to different platforms while still achieving high performance. We present OpenABL, a domain-specific language for portable, highperformance, parallel agent modeling. It comprises an easy-to-program language that relies on high-level abstractions for programmability and explicitly exploits agent parallelism to deliver high performance. A sourceto-source compiler translates the input code to a high-level intermediate representation exposing parallelism, locality and synchronization, and, thanks to an architecture based on pluggable backends, generates target code for multi-core CPUs, GPUs, large clusters and cloud systems. OpenABL has been evaluated on six applications from various fields such as ecology, animation, and social sciences. The generated code scales to large clusters and performs similarly to handwritten target-specific code, while requiring significantly fewer lines of codes.

PHP is a dynamically typed programming language commonly used for the server-side implementation of web applications. Approachability and ease of deployment have made PHP one of the most widely used scripting languages for the web, powering important web applications such as WordPress, Wikipedia, and Facebook. PHP's highly dynamic nature, while providing useful language features, also makes it hard to optimize statically. This paper reports on the implementation of purely static bytecode optimizations for PHP 7, the last major version of PHP. We discuss the challenge of integrating classical compiler optimizations, which have been developed in the context of statically-typed languages, into a programming language that is dynamically and weakly typed, and supports a plethora of dynamic language features. Based on a careful analysis of language semantics, we adapt static single assignment (SSA) form for use in PHP. Combined with type inference, this allows type-based specialization of instructions, as well as the application of various classical SSA-enabled compiler optimizations such as constant propagation or dead code elimination. We evaluate the impact of the proposed static optimizations on a wide collection of programs, including micro-benchmarks, libraries and web frameworks. Despite the dynamic nature of PHP, our approach achieves an average speedup of 50% on microbenchmarks, 13% on computationally intensive libraries, as well as 1.1% (MediaWiki) and 3.5% (WordPress) on web applications.

Agent-based simulations represent an effective scientific tool, with numerous applications from social sciences to biology, which aims to emulate or predict complex phenomena through a set of simple rules performed by multiple agents. To simulate a large number of agents with complex models, practitioners have developed high-performance parallel implementations, often specialized for particular scenarios and target hardware. It is, however, difficult to obtain portable simulations, which achieve high performance and at the same time are easy to write and to reproduce on different hardware. This article gives a complete presentation of OpenABL, a domain-specific language and a compiler for agent-based simulations that enable users to achieve high-performance parallel and distributed agent simulations with a simple and portable programming environment. OpenABL is comprised of (1) an easy-to-program language, which relies on domain abstractions and explicitly exposes agent parallelism, synchronization and locality, (2) a source-to-source compiler, and (3) a set of pluggable compiler backends, which generate target code for multi-core CPUs, GPUs, and cloud-based systems. We evaluate OpenABL on simulations from different fields. In particular, our analysis includes predator-prey and keratinocyte, two complex simulations with multiple step functions, heterogeneous agent types, and dynamic creation and removal of agents. The results show that OpenABL-generated codes are portable to different platforms, perform similarly to manual target-specific implementations, and require significantly fewer lines of codes.

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