1,377 research outputs found
Towards a Compiler for Reals
Numerical software, common in scientific computing or embedded systems, inevitably uses a finite-precision approximation of the real arithmetic in which most algorithms are designed. In many applications, the roundoff errors introduced by finite-precision arithmetic are not the only source of inaccuracy, and measurement and other input errors further increase the uncertainty of the computed results. Adequate tools are needed to help users select suitable data types and evaluate the provided accuracy, especially for safety-critical applications. We present a source-to-source compiler called Rosa that takes as input a real-valued program with error specifications and synthesizes code over an appropriate floating-point or fixed-point data type. The main challenge of such a compiler is a fully automated, sound, and yet accurate-enough numerical error estimation. We introduce a unified technique for bounding roundoff errors from floating-point and fixed-point arithmetic of various precisions. The technique can handle nonlinear arithmetic, determine closed-form symbolic invariants for unbounded loops, and quantify the effects of discontinuities on numerical errors. We evaluate Rosa on a number of benchmarks from scientific computing and embedded systems and, comparing it to the state of the art in automated error estimation, show that it presents an interesting tradeoff between accuracy and performance
The CIAO multiparadigm compiler and system: A progress report
Abstract is not available
A Verified Certificate Checker for Finite-Precision Error Bounds in Coq and HOL4
Being able to soundly estimate roundoff errors of finite-precision
computations is important for many applications in embedded systems and
scientific computing. Due to the discrepancy between continuous reals and
discrete finite-precision values, automated static analysis tools are highly
valuable to estimate roundoff errors. The results, however, are only as correct
as the implementations of the static analysis tools. This paper presents a
formally verified and modular tool which fully automatically checks the
correctness of finite-precision roundoff error bounds encoded in a certificate.
We present implementations of certificate generation and checking for both Coq
and HOL4 and evaluate it on a number of examples from the literature. The
experiments use both in-logic evaluation of Coq and HOL4, and execution of
extracted code outside of the logics: we benchmark Coq extracted unverified
OCaml code and a CakeML-generated verified binary
Relay: A New IR for Machine Learning Frameworks
Machine learning powers diverse services in industry including search,
translation, recommendation systems, and security. The scale and importance of
these models require that they be efficient, expressive, and portable across an
array of heterogeneous hardware devices. These constraints are often at odds;
in order to better accommodate them we propose a new high-level intermediate
representation (IR) called Relay. Relay is being designed as a
purely-functional, statically-typed language with the goal of balancing
efficient compilation, expressiveness, and portability. We discuss the goals of
Relay and highlight its important design constraints. Our prototype is part of
the open source NNVM compiler framework, which powers Amazon's deep learning
framework MxNet
Joint Compressed Sensing and Manipulation of Wireless Emissions with Intelligent Surfaces
Programmable, intelligent surfaces can manipulate electromagnetic waves
impinging upon them, producing arbitrarily shaped reflection, refraction and
diffraction, to the benefit of wireless users. Moreover, in their recent form
of HyperSurfaces, they have acquired inter-networking capabilities, enabling
the Internet of Material Properties with immense potential in wireless
communications. However, as with any system with inputs and outputs, accurate
sensing of the impinging wave attributes is imperative for programming
HyperSurfaces to obtain a required response. Related solutions include field
nano-sensors embedded within HyperSurfaces to perform minute measurements over
the area of the HyperSurface, as well as external sensing systems. The present
work proposes a sensing system that can operate without such additional
hardware. The novel scheme programs the HyperSurface to perform compressed
sensing of the impinging wave via simple one-antenna power measurements. The
HyperSurface can jointly be programmed for both wave sensing and wave
manipulation duties at the same time. Evaluation via simulations validates the
concept and highlight its promising potential.Comment: Published at IEEE DCOSS 2019 / IoT4.0 workshop
(https://www.dcoss.org/workshops.html). Funded by the European Union via the
Horizon 2020: Future Emerging Topics - Research and Innovation Action call
(FETOPEN-RIA), grant EU736876, project VISORSURF (http://www.visorsurf.eu
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