1,313 research outputs found
Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code
The current trend in next-generation exascale systems goes towards
integrating a wide range of specialized (co-)processors into traditional
supercomputers. However, the integration of different specialized devices
increases the degree of heterogeneity and the complexity in programming such
type of systems. Due to the efficiency of heterogeneous systems in terms of
Watt and FLOPS per surface unit, opening the access of heterogeneous platforms
to a wider range of users is an important problem to be tackled. In order to
bridge the gap between heterogeneous systems and programmers, in this paper we
propose a machine learning-based approach to learn heuristics for defining
transformation strategies of a program transformation system. Our approach
proposes a novel combination of reinforcement learning and classification
methods to efficiently tackle the problems inherent to this type of systems.
Preliminary results demonstrate the suitability of the approach for easing the
programmability of heterogeneous systems.Comment: Part of the Program Transformation for Programmability in
Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March
2016, 9 pages, LaTe
Type-driven automated program transformations and cost modelling for optimising streaming programs on FPGAs
In this paper we present a novel approach to program optimisation based on compiler-based type-driven program transformations and a fast and accurate cost/performance model for the target architecture. We target streaming programs for the problem domain of scientific computing, such as numerical weather prediction. We present our theoretical framework for type-driven program transformation, our target high-level language and intermediate representation languages and the cost model and demonstrate the effectiveness of our approach by comparison with a commercial toolchain
An extensible benchmark and tooling for comparing reverse engineering approaches
Various tools exist to reverse engineer software source code and generate design information, such as UML projections. Each has specific strengths and weaknesses, however no standardised benchmark exists that can be used to evaluate and compare their performance and effectiveness in a systematic manner. To facilitate such comparison in this paper we introduce the Reverse Engineering to Design Benchmark (RED-BM), which consists of a comprehensive set of Java-based targets for reverse engineering and a formal set of performance measures with which tools and approaches can be analysed and ranked. When used to evaluate 12 industry standard tools performance figures range from 8.82\% to 100\% demonstrating the ability of the benchmark to differentiate between tools. To aid the comparison, analysis and further use of reverse engineering XMI output we have developed a parser which can interpret the XMI output format of the most commonly used reverse engineering applications, and is used in a number of tools
P4CEP: Towards In-Network Complex Event Processing
In-network computing using programmable networking hardware is a strong trend
in networking that promises to reduce latency and consumption of server
resources through offloading to network elements (programmable switches and
smart NICs). In particular, the data plane programming language P4 together
with powerful P4 networking hardware has spawned projects offloading services
into the network, e.g., consensus services or caching services. In this paper,
we present a novel case for in-network computing, namely, Complex Event
Processing (CEP). CEP processes streams of basic events, e.g., stemming from
networked sensors, into meaningful complex events. Traditionally, CEP
processing has been performed on servers or overlay networks. However, we argue
in this paper that CEP is a good candidate for in-network computing along the
communication path avoiding detouring streams to distant servers to minimize
communication latency while also exploiting processing capabilities of novel
networking hardware. We show that it is feasible to express CEP operations in
P4 and also present a tool to compile CEP operations, formulated in our P4CEP
rule specification language, to P4 code. Moreover, we identify challenges and
problems that we have encountered to show future research directions for
implementing full-fledged in-network CEP systems.Comment: 6 pages. Author's versio
EbbRT: a customizable operating system for cloud applications
Efficient use of hardware requires operating system components be customized to the application workload. Our general purpose operating systems are ill-suited for this task. We present Genesis, a new operating system that enables per-application customizations for cloud applications. Genesis achieves this through a novel heterogeneous distributed structure, a partitioned object model, and an event-driven execution environment. This paper describes the design and prototype implementation of Genesis, and evaluates its ability to improve the performance of common cloud applications. The evaluation of the Genesis prototype demonstrates memcached, run within a VM, can outperform memcached run on an unvirtualized Linux. The prototype evaluation also demonstrates an 14% performance improvement of a V8 JavaScript engine benchmark, and a node.js webserver that achieves a 50% reduction in 99th percentile latency compared to it run on Linux
EbbRT: a framework for building per-application library operating systems
Efficient use of high speed hardware requires operating system components be customized to the application work- load. Our general purpose operating systems are ill-suited for this task. We present EbbRT, a framework for constructing per-application library operating systems for cloud applications. The primary objective of EbbRT is to enable high-performance in a tractable and maintainable fashion. This paper describes the design and implementation of EbbRT, and evaluates its ability to improve the performance of common cloud applications. The evaluation of the EbbRT prototype demonstrates memcached, run within a VM, can outperform memcached run on an unvirtualized Linux. The prototype evaluation also demonstrates an 14% performance improvement of a V8 JavaScript engine benchmark, and a node.js webserver that achieves a 50% reduction in 99th percentile latency compared to it run on Linux
Static analysis of energy consumption for LLVM IR programs
Energy models can be constructed by characterizing the energy consumed by
executing each instruction in a processor's instruction set. This can be used
to determine how much energy is required to execute a sequence of assembly
instructions, without the need to instrument or measure hardware.
However, statically analyzing low-level program structures is hard, and the
gap between the high-level program structure and the low-level energy models
needs to be bridged. We have developed techniques for performing a static
analysis on the intermediate compiler representations of a program.
Specifically, we target LLVM IR, a representation used by modern compilers,
including Clang. Using these techniques we can automatically infer an estimate
of the energy consumed when running a function under different platforms, using
different compilers.
One of the challenges in doing so is that of determining an energy cost of
executing LLVM IR program segments, for which we have developed two different
approaches. When this information is used in conjunction with our analysis, we
are able to infer energy formulae that characterize the energy consumption for
a particular program. This approach can be applied to any languages targeting
the LLVM toolchain, including C and XC or architectures such as ARM Cortex-M or
XMOS xCORE, with a focus towards embedded platforms. Our techniques are
validated on these platforms by comparing the static analysis results to the
physical measurements taken from the hardware. Static energy consumption
estimation enables energy-aware software development, without requiring
hardware knowledge
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