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Autore principale: Salishev, Sergey
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2512.22676
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author Salishev, Sergey
author_facet Salishev, Sergey
contents This thesis develops signal-processing algorithms and implementation schemes under constraints of minimal parallelism and memory space, with the goal of improving energy efficiency of low-power computing hardware. We propose (i) a power/energy consumption model for clocked CMOS logic that supports selecting optimal parallelism, (ii) integer-friendly approximation methods for elementary functions that reduce lookup-table size via constrained piecewise-polynomial (quasi-spline) constructions with accuracy guarantees, (iii) provably conflict-free data placement and execution order for mixed-radix streaming FFT on multi-bank and single-port memories, including a self-sorting FFT variant, and (iv) a parallelism/memory analysis of the fast Schur algorithm for superfast Toeplitz system solving, motivated by echo-cancellation workloads. The results provide constructive theorems, schedules, and design trade-offs enabling efficient specialized accelerators.
format Preprint
id arxiv_https___arxiv_org_abs_2512_22676
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Synthesis of signal processing algorithms with constraints on minimal parallelism and memory space
Salishev, Sergey
Signal Processing
Hardware Architecture
Distributed, Parallel, and Cluster Computing
Numerical Analysis
68W10 (Primary) 65T50, 65D15 (Secondary)
B.8.2; F.2.1
This thesis develops signal-processing algorithms and implementation schemes under constraints of minimal parallelism and memory space, with the goal of improving energy efficiency of low-power computing hardware. We propose (i) a power/energy consumption model for clocked CMOS logic that supports selecting optimal parallelism, (ii) integer-friendly approximation methods for elementary functions that reduce lookup-table size via constrained piecewise-polynomial (quasi-spline) constructions with accuracy guarantees, (iii) provably conflict-free data placement and execution order for mixed-radix streaming FFT on multi-bank and single-port memories, including a self-sorting FFT variant, and (iv) a parallelism/memory analysis of the fast Schur algorithm for superfast Toeplitz system solving, motivated by echo-cancellation workloads. The results provide constructive theorems, schedules, and design trade-offs enabling efficient specialized accelerators.
title Synthesis of signal processing algorithms with constraints on minimal parallelism and memory space
topic Signal Processing
Hardware Architecture
Distributed, Parallel, and Cluster Computing
Numerical Analysis
68W10 (Primary) 65T50, 65D15 (Secondary)
B.8.2; F.2.1
url https://arxiv.org/abs/2512.22676