Remote attestation is one of the core functionalities provided by trusted computing platforms. It holds the promise of enabling a variety of novel applications. However, current techniques for remote attestation are static, inexpressive and fundamentally incompatible with today's heterogeneous distributed computing environments and commodity open systems. Using language-based virtual machines enables the remote attestation of complex, dynamic, and high-level program properties --- in a platform-independent way. We call this semantic remote attestation. This enables a number of novel applications that distribute trust dynamically. We have implemented a prototype framework for semantic remote attestation, and present two example applications built on it --- a peer-to-peer network protocol, and a distributed computing application.

. This paper presents a high-speed method for computing elementary functions using parallel table lookups and multi-operand addition. Increasing the number of tables and inputs to the multi-operand adder significantly reduces the amount of memory required. Symmetry and leading zeros in the table coefficients are used to reduce the amount of memory even further. This method has a closed-form solution for the table entries and can be applied to any differentiable function. For 24-bit operands, this method requires two to three orders of magnitude less memory than conventional table lookups. Keywords: Elementary functions, table lookups, approximations, multi-operand addition, computer arithmetic, hardware design. 1. Introduction Elementary function approximations are important in scientific computing, computer graphics, and digital signal processing applications. In the systolic array implementation of Cholesky decomposition, presented in [1], 30% of the cells approximate reciprocals...

There are two fundamental limitations in software testing, known as the reliable test set problem and the oracle problem. Fault-based testing is an attempt by Morell to alleviate the reliable test set problem. In this paper, we propose to enhance fault-based testing to alleviate the oracle problem as well. We present an integrated method that combines metamorphic testing with fault-based testing using real and symbolic inputs.

This paper presents a methodology for designing bipartite tables for accurate function approximation. Bipartite tables use two parallel table lookups to obtain a carry-save (borrow-save) function approximation. A carry propagate adder can then convert this approximation to a two's complement number or the approximation can be directly Booth encoded. Our method for designing bipartite tables, called the Symmetric Bipartite Table Method, utilizes symmetry in the table entries to reduce the overall memory requirements. It has several advantages over previous bipartite table methods in that it (1) provides a closed form solution for the table entries, (2) has tight bounds on the maximum absolute error, (3) requires smaller table lookups to achieve a given accuracy, and (4) can be applied to a wide range of functions. Compared to conventional table lookups, the symmetric bipartite tables presented in this paper are 15.0 to 41.7 times smaller when the operand size is 16 bits and 99.1 to 273....

. This document is an excerpt from the current hypertext version of an article that appeared in Walter Gautschi (ed.), Mathematics of Computation 1943--1993: A Half-Century of Computational Mathematics, Proceedings of Symposia in Applied Mathematics 48, American Mathematical Society, Providence, RI 02940, 1994. The symposium was held at the University of British Columbia August 9--13, 1993, in honor of the fiftieth anniversary of the journal Mathematics of Computation. The original abstract follows. Higher transcendental functions continue to play varied and important roles in investigations by engineers, mathematicians, scientists and statisticians. The purpose of this paper is to assist in locating useful approximations and software for the numerical generation of these functions, and to offer some suggestions for future developments in this field. 5.9. Mathieu, Lam'e, and Spheroidal Wave Functions. 5.9.1. Characteristic Values of Mathieu's Equation. Software Packages:...

This paper deals with the computation of reciprocals, square roots, inverse square roots, and some elementary functions using small tables, small multipliers, and for some functions, a final "large" (almost full-length) multiplication. We propose a method that allows fast evaluation of these functions in double precision arithmetic. The strength of this method is that the same scheme allows the computation of all these functions. Our method is mainly interesting for designing special purpose circuits, since it does not allow a simple implementation of the four rounding modes required by the IEEE-754 standard for floating-point arithmetic.

It is not uncommon to encounter trigonometric functions of huge argument.Consider a simple spring problem, under no damping conditions, the motion can be described

An oracle is a mechanism against which the tester can decide whether the outputs of the program for the executed test cases are correct. A fundamental problem of software testing is that, in many situations, the oracle is not available or too difficult to apply. A metamorphic testing (MT) method has been proposed to alleviate the oracle problem. MT is an automated testing method that employs expected properties of the target functions to test programs without human involvement. These properties are called metamorphic relations (MR). For a given problem, usually more than one MR can be identified. It is therefore interesting and very useful for practitioners to know how to select effective MRs that are good at detecting program defects. This article proposes a guideline for the select-ion of good MRs for automated testing. The effectiveness of our strategy has been investigated through case studies.

It is challenging to test machine learning (ML) applications, which are intended to learn properties of data sets where the correct answers are not already known. In the absence of a test oracle, one approach to testing these applications is to use metamorphic testing, in which properties of the application are exploited to define transformation functions on the input, such that the new output will be unchanged or can easily be predicted based on the original output; if the output is not as expected, then a defect must exist in the application. Here, we seek to enumerate and classify the metamorphic properties of some machine learning algorithms, and demonstrate how these can be applied to reveal defects in the applications of interest. In addition to the results of our testing, we present a set of properties that can be used to define these metamorphic relationships so that metamorphic testing can be used as a general approach to testing machine learning applications. 1

A table-based method for high-speed function approximation in single-precision floating-point format is presented in this paper. Our focus is the approximation of reciprocal, square root, square root reciprocal, exponentials, logarithms, trigonometric functions, powering (with a fixed exponent p), or special functions. The algorithm presented here combines table look-up, an enhanced minimax quadratic approximation, and an efficient evaluation of the second-degree polynomial (using a specialized squaring unit, redundant arithmetic, and multioperand addition). The execution times and area costs of an architecture implementing our method are estimated, showing the achievement of the fast execution times of linear approximation methods and the reduced area requirements of other second-degree interpolation algorithms. Moreover, the use of an enhanced minimax approximation which, through an iterative process, takes into account the effect of rounding the polynomial coefficients to a finite size allows for a further reduction in the size of the look-up tables to be used, making our method very suitable for the implementation of an elementary function generator in state-ofthe-art DSPs or graphics processing units (GPUs).