2,234 research outputs found
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 Reconfigurable Vector Instruction Processor for Accelerating a Convection Parametrization Model on FPGAs
High Performance Computing (HPC) platforms allow scientists to model
computationally intensive algorithms. HPC clusters increasingly use
General-Purpose Graphics Processing Units (GPGPUs) as accelerators; FPGAs
provide an attractive alternative to GPGPUs for use as co-processors, but they
are still far from being mainstream due to a number of challenges faced when
using FPGA-based platforms. Our research aims to make FPGA-based high
performance computing more accessible to the scientific community. In this work
we present the results of investigating the acceleration of a particular
atmospheric model, Flexpart, on FPGAs. We focus on accelerating the most
computationally intensive kernel from this model. The key contribution of our
work is the architectural exploration we undertook to arrive at a solution that
best exploits the parallelism available in the legacy code, and is also
convenient to program, so that eventually the compilation of high-level legacy
code to our architecture can be fully automated. We present the three different
types of architecture, comparing their resource utilization and performance,
and propose that an architecture where there are a number of computational
cores, each built along the lines of a vector instruction processor, works best
in this particular scenario, and is a promising candidate for a generic
FPGA-based platform for scientific computation. We also present the results of
experiments done with various configuration parameters of the proposed
architecture, to show its utility in adapting to a range of scientific
applications.Comment: This is an extended pre-print version of work that was presented at
the international symposium on Highly Efficient Accelerators and
Reconfigurable Technologies (HEART2014), Sendai, Japan, June 911, 201
Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design
The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface
Static Analysis-based Debugging, Certification, Testing, and Optimization with CiaoPP
Facilitate the development of safe, efficient programs.
Approach:
•Next-generation, higher-level, multiparadigm prog. languages.
•Improved program development environments.
•A framework (CiaoPP) which integrates:
•Debugging.
•Verification and certification.
•Testing.
•Optimization (optimized compilation, parallelization, ...
Generalizing input-driven languages: theoretical and practical benefits
Regular languages (RL) are the simplest family in Chomsky's hierarchy. Thanks
to their simplicity they enjoy various nice algebraic and logic properties that
have been successfully exploited in many application fields. Practically all of
their related problems are decidable, so that they support automatic
verification algorithms. Also, they can be recognized in real-time.
Context-free languages (CFL) are another major family well-suited to
formalize programming, natural, and many other classes of languages; their
increased generative power w.r.t. RL, however, causes the loss of several
closure properties and of the decidability of important problems; furthermore
they need complex parsing algorithms. Thus, various subclasses thereof have
been defined with different goals, spanning from efficient, deterministic
parsing to closure properties, logic characterization and automatic
verification techniques.
Among CFL subclasses, so-called structured ones, i.e., those where the
typical tree-structure is visible in the sentences, exhibit many of the
algebraic and logic properties of RL, whereas deterministic CFL have been
thoroughly exploited in compiler construction and other application fields.
After surveying and comparing the main properties of those various language
families, we go back to operator precedence languages (OPL), an old family
through which R. Floyd pioneered deterministic parsing, and we show that they
offer unexpected properties in two fields so far investigated in totally
independent ways: they enable parsing parallelization in a more effective way
than traditional sequential parsers, and exhibit the same algebraic and logic
properties so far obtained only for less expressive language families
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High integrity hardware-software codesign
Programmable logic devices (PLDs) are increasing in complexity and speed, and are being used as important components in safety-critical systems. Methods for developing high-integrity software for these systems are well-known, but this is not true for programmable logic. We propose a process for developing a system incorporating software and PLDs, suitable for safety critical systems of the highest levels of integrity. This process incorporates the use of Synchronous Receptive Process Theory as a semantic basis for specifying and proving properties of programs executing on PLDs, and extends the use of SPARK Ada from a programming language for safety-critical systems software to cover the interface between software and programmable logic. We have validated this approach through the specification and development of a substantial safety-critical system incorporating both software and programmable logic components, and the development of tools to support this work. This enables us to claim that the methods demonstrated are not only feasible but also scale up to realistic system sizes, allowing development of such safety-critical software-hardware systems to the levels required by current system safety standards
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