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HW/SW Co-design of a PCM/PWM converter: a System Level Approach based in the SpecC Methodology

Daniel G. P. Petrini, Braz Izaias da Silva Junior

TL;DR

This paper demonstrates a system-level co-design workflow using the SpecC methodology to re-evaluate a PCM-to-PWM converter for Class-D audio amplifiers. By translating a C algorithm into SpecC, performing architecture exploration, and comparing HW, DSP, and software mappings, the study yields a hardware/software partition that satisfies real-time constraints at a lower cost than fully software or fully hardware alternatives. The work highlights the advantages of fast system-level simulation, automatic refinement, and early architectural insight, while also noting limitations such as the lack of automatic partitioning and a limited PE library in the evaluated tool version. Overall, the SpecC-based approach proves effective for generating implementable design proposals with actionable cost/performance trade-offs for moderate-complexity signal-processing systems.

Abstract

We present a case study applying the SpecC methodology within a system-level hardware/software co-design flow to a PCM-to-PWM converter, the core of a Class-D audio amplifier. The converter was modeled and explored with SpecC methodology to derive an HW/SW partition. Using system-level estimates and fast functional simulation, we evaluated mappings that meet real-time constraints while reducing estimated cost of an all-hardware solution and avoiding the expense of a purely software implementation on a high-end processor. Despite the design's moderate complexity, the results underline the value of system-level co-design for early architectural insight, rapid validation, and actionable cost/performance trade-offs. [Original work from 2005; formatting revised in 2025, with no changes to the results.]

HW/SW Co-design of a PCM/PWM converter: a System Level Approach based in the SpecC Methodology

TL;DR

This paper demonstrates a system-level co-design workflow using the SpecC methodology to re-evaluate a PCM-to-PWM converter for Class-D audio amplifiers. By translating a C algorithm into SpecC, performing architecture exploration, and comparing HW, DSP, and software mappings, the study yields a hardware/software partition that satisfies real-time constraints at a lower cost than fully software or fully hardware alternatives. The work highlights the advantages of fast system-level simulation, automatic refinement, and early architectural insight, while also noting limitations such as the lack of automatic partitioning and a limited PE library in the evaluated tool version. Overall, the SpecC-based approach proves effective for generating implementable design proposals with actionable cost/performance trade-offs for moderate-complexity signal-processing systems.

Abstract

We present a case study applying the SpecC methodology within a system-level hardware/software co-design flow to a PCM-to-PWM converter, the core of a Class-D audio amplifier. The converter was modeled and explored with SpecC methodology to derive an HW/SW partition. Using system-level estimates and fast functional simulation, we evaluated mappings that meet real-time constraints while reducing estimated cost of an all-hardware solution and avoiding the expense of a purely software implementation on a high-end processor. Despite the design's moderate complexity, the results underline the value of system-level co-design for early architectural insight, rapid validation, and actionable cost/performance trade-offs. [Original work from 2005; formatting revised in 2025, with no changes to the results.]
Paper Structure (11 sections, 8 figures, 5 tables)

This paper contains 11 sections, 8 figures, 5 tables.

Figures (8)

  • Figure 1: SpecC Models.
  • Figure 2: SpecC Constructions: (a)Behavior declaring, (b)Sequential execution, (c)Parallel execution, (d)Synchronization elements.
  • Figure 3: Class D digital amplification.
  • Figure 4: PCM-PWM conversion stages, which guide the subsequent behavior mapping: S0, S1, S2, and S3 (upsampling), LINE (linearization), and MOLD (noise shaping).
  • Figure 5: Connectivity between behaviors in the testbench for phase # 1 towards specification model.
  • ...and 3 more figures