Efficient Late Binding of Dynamic Function Compositions

Adaptive software becomes more and more important as computing is increasingly context-dependent. Runtime adaptability can be achieved by dynamically selecting and applying context-specific code. Role-oriented programming has been proposed as a paradigm to enable runtime adaptive software by design. Roles change the objects’ behavior at runtime and thus allow adapting the software to a given context. However, this increased variability and expressiveness has a direct impact on performance and memory consumption. We found a high overhead in the steady-state performance of executing compositions of adaptations. This paper presents a new approach to use run-time information to construct a dispatch plan that can be executed efficiently by the JVM. The concept of late binding is extended to dynamic function compositions. We evaluated the implementation with a benchmark for role-oriented programming languages leveraging context-dependent role semantics achieving a mean speedup of 2.79× over the regular implementation

GCC-Plugin for Automated Accelerator Generation and Integration on Hybrid FPGA-SoCs

In recent years, architectures combining a reconfigurable fabric and a general purpose processor on a single chip became increasingly popular. Such hybrid architectures allow extending embedded software with application specific hardware accelerators to improve performance and/or energy efficiency. Aiding system designers and programmers at handling the complexity of the required process of hardware/software (HW/SW) partitioning is an important issue. Current methods are often restricted, either to bare-metal systems, to subsets of mainstream programming languages, or require special coding guidelines, e.g., via annotations. These restrictions still represent a high entry barrier for the wider community of programmers that new hybrid architectures are intended for. In this paper we revisit HW/SW partitioning and present a seamless programming flow for unrestricted, legacy C code. It consists of a retargetable GCC plugin that automatically identifies code sections for hardware acceleration and generates code accordingly. The proposed workflow was evaluated on the Xilinx Zynq platform using unmodified code from an embedded benchmark suite.Comment: Presented at Second International Workshop on FPGAs for Software Programmers (FSP 2015) (arXiv:1508.06320

A Domain-Specific Language and Editor for Parallel Particle Methods

Domain-specific languages (DSLs) are of increasing importance in scientific high-performance computing to reduce development costs, raise the level of abstraction and, thus, ease scientific programming. However, designing and implementing DSLs is not an easy task, as it requires knowledge of the application domain and experience in language engineering and compilers. Consequently, many DSLs follow a weak approach using macros or text generators, which lack many of the features that make a DSL a comfortable for programmers. Some of these features---e.g., syntax highlighting, type inference, error reporting, and code completion---are easily provided by language workbenches, which combine language engineering techniques and tools in a common ecosystem. In this paper, we present the Parallel Particle-Mesh Environment (PPME), a DSL and development environment for numerical simulations based on particle methods and hybrid particle-mesh methods. PPME uses the meta programming system (MPS), a projectional language workbench. PPME is the successor of the Parallel Particle-Mesh Language (PPML), a Fortran-based DSL that used conventional implementation strategies. We analyze and compare both languages and demonstrate how the programmer's experience can be improved using static analyses and projectional editing. Furthermore, we present an explicit domain model for particle abstractions and the first formal type system for particle methods.Comment: Submitted to ACM Transactions on Mathematical Software on Dec. 25, 201

ConDRust: Scalable Deterministic Concurrency from Verifiable Rust Programs

SAT/SMT-solvers and model checkers automate formal verification of sequential programs. Formal reasoning about scalable concurrent programs is still manual and requires expert knowledge. But scalability is a fundamental requirement of current and future programs. Sequential imperative programs compose statements, function/method calls and control flow constructs. Concurrent programming models provide constructs for concurrent composition. Concurrency abstractions such as threads and synchronization primitives such as locks compose the individual parts of a concurrent program that are meant to execute in parallel. We propose to rather compose the individual parts again using sequential composition and compile this sequential composition into a concurrent one. The developer can use existing tools to formally verify the sequential program while the translated concurrent program provides the dearly requested scalability. Following this insight, we present ConDRust, a new programming model and compiler for Rust programs. The ConDRust compiler translates sequential composition into a concurrent composition based on threads and message-passing channels. During compilation, the compiler preserves the semantics of the sequential program along with much desired properties such as determinism. Our evaluation shows that our ConDRust compiler generates concurrent deterministic code that can outperform even non-deterministic programs by up to a factor of three for irregular algorithms that are particularly hard to parallelize