CAD Tools for the optimized design of custom VLSI wave digital filters

Jain, Rajeev; Goossens, Gert; Claesen, Luc; Vandewalle, Joos; Man, H. De; Gazsi, L.; Fettweis, A.

doi:10.1109/icassp.1985.1168164

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…In the literature, many works [19][20][21][22][23][24][25][26][27][28][29] have been proposed to obtain the discrete coefficient values such that the incurred additions are minimized. These works can be classified into two categories.…”

Section: Introductionmentioning

confidence: 99%

“…The works in [19][20][21][22][23] obtain very good result; however, they require impractically long times for optimizing high-order filters with wide wordlengths. Therefore, some researchers suggested to first design the optimum real-valued coefficients and then quantize them with the consideration of filter complexity [24][25][26][27][28][29]. We call these approaches the quantizationbased methods.…”

Section: Introductionmentioning

confidence: 99%

“…We call these approaches the quantizationbased methods. The results in [24][25][26][27][28][29] show that great amount of additions can be saved by exploiting the scaling factor exploration and local search in the neighbor of the real-valued coefficients.…”

Section: Introductionmentioning

confidence: 99%

“…The aforementioned quantization methods [24][25][26][27][28][29] are effective for minimizing the complexity of the quantized coefficients, but most of them cannot explicitly control the number of additions. If designers want to improve the quantization error with the price of exactly one more addition, most of the above methods cannot efficiently make such a tradeoff.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Complexity-Aware Quantization and Lightweight VLSI Implementation of FIR Filters

Kuo

Lin

2011

EURASIP J. Adv. Signal Process.

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The coefficient values and number representations of digital FIR filters have significant impacts on the complexity of their VLSI realizations and thus on the system cost and performance. So, making a good tradeoff between implementation costs and quantization errors is essential for designing optimal FIR filters. This paper presents our complexity-aware quantization framework of FIR filters, which allows the explicit tradeoffs between the hardware complexity and quantization error to facilitate FIR filter design exploration. A new common subexpression sharing method and systematic bit-serialization are also proposed for lightweight VLSI implementations. In our experiments, the proposed framework saves 49% ∼ 51% additions of the filters with 2's complement coefficients and 10% ∼ 20% of those with conventional signed-digit representations for comparable quantization errors. Moreover, the bit-serialization can reduce 33% ∼ 35% silicon area for less timing-critical applications.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Complexity-Aware Quantization and Lightweight VLSI Implementation of FIR Filters

Kuo

Lin

2011

EURASIP J. Adv. Signal Process.

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System design, optimization and intelligent code generation for standard digital signal processors

Genin¹,

Moortel²,

Desmet³

et al.

IEEE International Symposium on Circuits and Systems

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Custom design of a VLSI PCM-FDM transmultiplexer from system specifications to circuit layout using a computer-aided design system

Jain

Catthoor

Vanhoof

et al. 1986

IEEE J. Solid-State Circuits

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Absfrncr-The computer-aided design of a VLSI PCM-FDM transmultiplexer is presented. The entire design process from sysrem specifiearions to integrated circuit layout is carried out with the aid of specialized computer programs for analysis, synthesis and optimization at each design level: the firter network, the architecture and the circuit layout. These CAD tools support a top-down custom design methodology based on bit-serial architectures and standard cells. A customized architecture is constructed, which is integrated using a 5-pm CMOS cell library. The results are compared with a fully manual design and demonstrate the power of architecture based computer-aided design methodologies for VLSI filtering. By combining both synthesis as well as optimization aids at each design level, it is possible to achieve a high degree of automation while retaining an efficient use of silicon area, high throughput and moderate power consumption.

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CAD Tools for the optimized design of custom VLSI wave digital filters

Cited by 4 publications

References 6 publications

Complexity-Aware Quantization and Lightweight VLSI Implementation of FIR Filters

Complexity-Aware Quantization and Lightweight VLSI Implementation of FIR Filters

System design, optimization and intelligent code generation for standard digital signal processors

Custom design of a VLSI PCM-FDM transmultiplexer from system specifications to circuit layout using a computer-aided design system

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