An efficient hybrid engine to perform range analysis and allocate integer bit-widths for arithmetic circuits

Pang,; Radecka,; Zilic,

doi:10.1109/aspdac.2011.5722233

Cited by 18 publications

(12 citation statements)

References 12 publications

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“…While we have shown the binary approach limitations, there are applications to automated multi-sensor system integration focused on arithmetics [5], where the discrete-valued case is limited as well. To go beyond these limitations, we plan to explore the arithmetics-focused approaches that further account for precision [15] and range [16], as promising areas for future work. The developments in these areas would include the ability to reason about the sequential [17], memory-based systems [18] as well as those that tightly integrate significant DSP blocks [19].…”

Section: Discussionmentioning

confidence: 98%

Issues in Multi-valued Multi-modal Sensor Fusion

Janidarmian

Žilić

Radecka

2012

2012 IEEE 42nd International Symposium on Multiple-Valued Logic

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Fault-tolerance of embedded systems with sensors is a major concern in emerging cyber-physical systems, which could be operating in the harsh and hostile environments. Sensors are usually deployed with redundancy, but traditional double and triple redundancies lead us to high cost and energy consumption. In this paper, we first propose a SAT-based algorithm to solve the Multi-Modal Sensor Allocation problem (MMSA). Further, we present a heterogeneous backup scheme with low overhead. It is also shown that by properly tuning the sensors, their sensitivity towards errors decreases. We show that when MMSA problem is extended for n-valued sensors, the effectiveness of the solution can be improved.

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Section: Discussionmentioning

confidence: 98%

Issues in Multi-valued Multi-modal Sensor Fusion

Janidarmian

Žilić

Radecka

2012

2012 IEEE 42nd International Symposium on Multiple-Valued Logic

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“…Dynamic analysis methods evaluate the system by using input stimulus. This analysis suffers from unsafe, data dependent, and time-consuming estimations, which confine its applicability [8]. Static analysis, however, uses static characteristics of the inputs which are propagated through the system.…”

Section: Related Workmentioning

confidence: 99%

“…To have finiteprecision fixed-point implementations of such systems, range analysis (RA) is an essential and fundamental design step. The analysis characterizes the integer bitwidths (IB) for all the fixed-point variables such that no overflow and underflow occur [1][2][3][4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

AIOSC: Analytical Integer Word-length Optimization Based on System Characteristics for Recursive Fixed-Point Linear Time Invariant Systems

Grailoo

Alizadeh

2020

IJE

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The integer word-length optimization known as range analysis (RA) of the fixed-point designs is a challenging problem in high level synthesis and optimization of linear-time-invariant (LTI) systems. The analysis has significant effects on the resource usage, accuracy and efficiency of the final implementation, as well as the optimization time. Conventional methods in recursive LTI systems suffer from inaccurate range estimations due to dependency to symmetry or non-symmetry of the input range over zero, and involvement with parameter adjustments. The under estimations endanger the range safety, and generate a great error due to overflows. On the other hand, the over estimations increase the hardware costs, as well as weaken the signal, if the over estimated ranges are utilized in down-scaling. Therefore, in this paper, we propose an efficient, safe and more precise RA method to measure the range of both recursive and non-recursive fixed-point LTI systems through analytical formulation. Our main idea is to obtain the input sequences for which variables in the LTI system would be maximum and minimum. By applying these sequences to the system, the upper and lower bounds of the intended variables are obtained as the range. The proposed method enhances the bitwidths accuracy more than 34% in average in comparison with the state-of-the-arts. The results also show about 37% and 6% savings in the area and delay, respectively.

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“…It is elided because this speed comes at a high cost in precision [18]. Furthermore, the affine arithmetic technique does not, as such, yield concrete witnesses.…”

Section: Is Simulation Sufficient To Find Bugs In Filters?mentioning

confidence: 99%

“…While verification for a specific bit-width is one method for solving this problem, other works have considered interval arithmetic, affine arithmetic [8,13], spectral techniques [17], and combinations thereof [18].…”

Section: Related Workmentioning

confidence: 99%

A Bit Too Precise? Bounded Verification of Quantized Digital Filters

Cox

Sankaranarayanan

Chang

2012

Tools and Algorithms for the Construction and Analysis of Systems

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Abstract. Digital filters are simple yet ubiquitous components of a wide variety of digital processing and control systems. Errors in the filters can be catastrophic. Traditionally digital filters have been verified using methods from control theory and extensive testing. We study two alternative verification techniques: bitprecise analysis and real-valued error approximations. In this paper, we empirically evaluate several variants of these two fundamental approaches for verifying fixed-point implementations of digital filters. We design our comparison to reveal the best possible approach towards verifying real-world designs of infinite impulse response (IIR) digital filters. Our study reveals broader insights into cases where bit-reasoning is absolutely necessary and suggests efficient approaches using modern satisfiability-modulo-theories (SMT) solvers.

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An efficient hybrid engine to perform range analysis and allocate integer bit-widths for arithmetic circuits

Cited by 18 publications

References 12 publications

Issues in Multi-valued Multi-modal Sensor Fusion

Issues in Multi-valued Multi-modal Sensor Fusion

AIOSC: Analytical Integer Word-length Optimization Based on System Characteristics for Recursive Fixed-Point Linear Time Invariant Systems

A Bit Too Precise? Bounded Verification of Quantized Digital Filters

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