6,182 research outputs found
JIST: just-in-time scheduling translation for parallel processors
The application fields of bytecode virtual machines and VLIW processors overlap in the area of embedded and mobile systems, where the two technologies offer different benefits, namely high code portability, low power consumption and reduced hardware cost. Dynamic compilation makes it possible to bridge the gap between the two technologies, but special attention must be paid to software instruction scheduling, a must for the VLIW architectures. We have implemented JIST, a Virtual Machine and JIT compiler for Java Bytecode targeted to a VLIW processor. We show the impact of various optimizations on the performance of code compiled with JIST through the experimental study on a set of benchmark programs. We report significant speedups, and increments in the number of instructions issued per cycle up to 50% with respect to the non-scheduling version of the JITcompiler. Further optimizations are discussed
Ahead-of-Time Algebraic Compilation for Safety-Critical Java
In recent years Java has been increasingly considered as a language for safety-critical embedded systems. However, some features of Java are unsuitable for such systems. This has resulted in the creation of Safety-Critical Java (SCJ), which facilitates the development of certifiable real-time and embedded Java programs. SCJ uses different scheduling and memory management models to standard Java, so it requires a specialised virtual machine (SCJVM). A common
approach is to compile Java bytecode program to a native language, usually C, ahead-of-time for greater performance on low-resource embedded systems.
Given the safety-critical nature of the applications, it must be ensured that the virtual machine is correct. However, so far, formal verification has not been applied to any SCJVM. This thesis contributes to the formal verification of SCJVMs that utilise ahead-of-time compilation by presenting a verification of compilation from Java bytecode to C.
The approach we adopt is an adaptation of the algebraic approach developed by Sampaio and Hoare. We start with a formal specification of an SCJVM executing the bytecodes of a program, and transform it, through the application of proven compilation rules, to a representation of the target C code. Thus, our contributions are a formal specification of an SCJVM, a set of compilation rules with proofs, and a strategy for applying those compilation rules.
Our compilation strategy can be used as the basis for an implementation of an ahead-of-time compiling SCJVM, or verification of an existing implementation. Additionally, our formal model of an SCJVM may be used as a specification for creating an interpreting SCJVM. To ensure the
applicability of our results, we base our work on icecap, the only currently available SCJVM that is open source and up-to-date with the SCJ standard
Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models
The upcoming many-core architectures require software developers to exploit
concurrency to utilize available computational power. Today's high-level
language virtual machines (VMs), which are a cornerstone of software
development, do not provide sufficient abstraction for concurrency concepts. We
analyze concrete and abstract concurrency models and identify the challenges
they impose for VMs. To provide sufficient concurrency support in VMs, we
propose to integrate concurrency operations into VM instruction sets.
Since there will always be VMs optimized for special purposes, our goal is to
develop a methodology to design instruction sets with concurrency support.
Therefore, we also propose a list of trade-offs that have to be investigated to
advise the design of such instruction sets.
As a first experiment, we implemented one instruction set extension for
shared memory and one for non-shared memory concurrency. From our experimental
results, we derived a list of requirements for a full-grown experimental
environment for further research
Concurrent Models for Object Execution
In previous work we developed a framework of computational models for the
concurrent execution of functions on different levels of abstraction. It shows
that the traditional sequential execution of function is just a possible
implementation of an abstract computational model that allows for the
concurrent execution of function. We use this framework as base for the
development of abstract computational models that allow for the concurrent
execution of objects
A Survey on Compiler Autotuning using Machine Learning
Since the mid-1990s, researchers have been trying to use machine-learning
based approaches to solve a number of different compiler optimization problems.
These techniques primarily enhance the quality of the obtained results and,
more importantly, make it feasible to tackle two main compiler optimization
problems: optimization selection (choosing which optimizations to apply) and
phase-ordering (choosing the order of applying optimizations). The compiler
optimization space continues to grow due to the advancement of applications,
increasing number of compiler optimizations, and new target architectures.
Generic optimization passes in compilers cannot fully leverage newly introduced
optimizations and, therefore, cannot keep up with the pace of increasing
options. This survey summarizes and classifies the recent advances in using
machine learning for the compiler optimization field, particularly on the two
major problems of (1) selecting the best optimizations and (2) the
phase-ordering of optimizations. The survey highlights the approaches taken so
far, the obtained results, the fine-grain classification among different
approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our
Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated
quarterly here (Send me your new published papers to be added in the
subsequent version) History: Received November 2016; Revised August 2017;
Revised February 2018; Accepted March 2018
Network Virtual Machine (NetVM): A New Architecture for Efficient and Portable Packet Processing Applications
A challenge facing network device designers, besides increasing the speed of network gear, is improving its programmability in order to simplify the implementation of new applications (see for example, active networks, content networking, etc). This paper presents our work on designing and implementing a virtual network processor, called NetVM, which has an instruction set optimized for packet processing applications, i.e., for handling network traffic. Similarly to a Java Virtual Machine that virtualizes a CPU, a NetVM virtualizes a network processor. The NetVM is expected to provide a compatibility layer for networking tasks (e.g., packet filtering, packet counting, string matching) performed by various packet processing applications (firewalls, network monitors, intrusion detectors) so that they can be executed on any network device, ranging from expensive routers to small appliances (e.g. smart phones). Moreover, the NetVM will provide efficient mapping of the elementary functionalities used to realize the above mentioned networking tasks upon specific hardware functional units (e.g., ASICs, FPGAs, and network processing elements) included in special purpose hardware systems possibly deployed to implement network devices
LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing
LEGaTO is a three-year EU H2020 project which started in December 2017. The LEGaTO project will leverage task-based programming models to provide a software ecosystem for Made-in-Europe heterogeneous hardware composed of CPUs, GPUs, FPGAs and dataflow engines. The aim is to attain one order of magnitude energy savings from the edge to the converged cloud/HPC.Peer ReviewedPostprint (author's final draft
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