2,646 research outputs found
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components
Approximate computing is an emerging paradigm for developing highly
energy-efficient computing systems such as various accelerators. In the
literature, many libraries of elementary approximate circuits have already been
proposed to simplify the design process of approximate accelerators. Because
these libraries contain from tens to thousands of approximate implementations
for a single arithmetic operation it is intractable to find an optimal
combination of approximate circuits in the library even for an application
consisting of a few operations. An open problem is "how to effectively combine
circuits from these libraries to construct complex approximate accelerators".
This paper proposes a novel methodology for searching, selecting and combining
the most suitable approximate circuits from a set of available libraries to
generate an approximate accelerator for a given application. To enable fast
design space generation and exploration, the methodology utilizes machine
learning techniques to create computational models estimating the overall
quality of processing and hardware cost without performing full synthesis at
the accelerator level. Using the methodology, we construct hundreds of
approximate accelerators (for a Sobel edge detector) showing different but
relevant tradeoffs between the quality of processing and hardware cost and
identify a corresponding Pareto-frontier. Furthermore, when searching for
approximate implementations of a generic Gaussian filter consisting of 17
arithmetic operations, the proposed approach allows us to identify
approximately highly important implementations from possible
solutions in a few hours, while the exhaustive search would take four months on
a high-end processor.Comment: Accepted for publication at the Design Automation Conference 2019
(DAC'19), Las Vegas, Nevada, US
A case study for NoC based homogeneous MPSoC architectures
The many-core design paradigm requires flexible and modular hardware and software components to provide the required scalability to next-generation on-chip multiprocessor architectures. A multidisciplinary approach is necessary to consider all the interactions between the different components of the design. In this paper, a complete design methodology that tackles at once the aspects of system level modeling, hardware architecture, and programming model has been successfully used for the implementation of a multiprocessor network-on-chip (NoC)-based system, the NoCRay graphic accelerator. The design, based on 16 processors, after prototyping with field-programmable gate array (FPGA), has been laid out in 90-nm technology. Post-layout results show very low power, area, as well as 500 MHz of clock frequency. Results show that an array of small and simple processors outperform a single high-end general purpose processo
Metamorphic Domain-Specific Languages: A Journey Into the Shapes of a Language
External or internal domain-specific languages (DSLs) or (fluent) APIs?
Whoever you are -- a developer or a user of a DSL -- you usually have to choose
your side; you should not! What about metamorphic DSLs that change their shape
according to your needs? We report on our 4-years journey of providing the
"right" support (in the domain of feature modeling), leading us to develop an
external DSL, different shapes of an internal API, and maintain all these
languages. A key insight is that there is no one-size-fits-all solution or no
clear superiority of a solution compared to another. On the contrary, we found
that it does make sense to continue the maintenance of an external and internal
DSL. The vision that we foresee for the future of software languages is their
ability to be self-adaptable to the most appropriate shape (including the
corresponding integrated development environment) according to a particular
usage or task. We call metamorphic DSL such a language, able to change from one
shape to another shape
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