Garbage collected programming languages, such as Python and C#, have accelerated software development. These modern languages increase productivity and software reliability as they provide high-level data representation and control structures. Modern languages are widely used in software development for mobile, desktop, and server devices, but their adoption is limited in real-time embedded systems. There is clear interest in supporting modern languages in embedded devices as emerging markets, like the Internet of Things, demand ever smarter and more reliable products. Multiple commercial and open-source projects, such as Zerynth and MicroPython, are attempting to provide support. But these projects rely on software garbage collectors that impose high overheads and introduce unpredictable pauses, preventing their use in many embedded applications. These limitations arise from the unsuitability of conventional processors for performing efficient, predictable garbage collection. We propose the Integrated Hardware Garbage Collector (IHGC); a garbage collector tightly coupled with the processor that runs continuously in the background. Further, we introduce a static analysis technique to guarantee that real-time programs are never paused by the collector. Our design allocates a memory cycle to the collector when the processor is not using the memory. The IHGC achieves this by careful division of collection work into single-memory-access steps that are interleaved with the processor’s memory accesses. As a result, our collector eliminates run-time overheads and enables real-time program analysis. The principles behind the IHGC can be used in conjunction with existing architectures. For example, we simulated the IHGC alongside the ARMv6-M architecture. Compared to a conventional processor, our experiments indicate that the IHGC offers 1.5–7 times better performance for programs that rely on garbage collection. The IHGC delivers the benefits of garbage-collected languages with real-time performance but without the complexity and overheads inherent in software collectors.

中文翻译：

---

集成硬件垃圾收集

垃圾收集的编程语言，如 Python 和 C#，加速了软件开发。这些现代语言提高了生产力和软件可靠性，因为它们提供了高级数据表示和控制结构。现代语言广泛用于移动、桌面和服务器设备的软件开发，但它们在实时嵌入式系统中的采用受到限制。随着物联网等新兴市场需要更智能、更可靠的产品，人们对在嵌入式设备中支持现代语言有着明显的兴趣。多个商业和开源项目，例如 Zerynth 和 MicroPython，正在尝试提供支持。但是这些项目依赖于软件垃圾收集器，这会带来高昂的开销并引入不可预测的暂停，从而阻止它们在许多嵌入式应用程序中的使用。这些限制源于传统处理器不适合执行高效、可预测的垃圾收集。我们提出了集成硬件垃圾收集器（IHGC）；与在后台连续运行的处理器紧密耦合的垃圾收集器。此外，我们引入了一种静态分析技术，以保证实时程序永远不会被收集器暂停。当处理器不使用内存时，我们的设计会为收集器分配一个内存周期。IHGC 通过将收集工作仔细划分为与处理器的内存访问交错的单个内存访问步骤来实现这一点。因此，我们的收集器消除了运行时开销并支持实时程序分析。IHGC 背后的原理可以与现有架构结合使用。例如，我们模拟了 IHGC 和 ARMv6-M 架构。与传统处理器相比，我们的实验表明 IHGC 为依赖垃圾收集的程序提供了 1.5-7 倍的性能。IHGC 提供了具有实时性能的垃圾收集语言的优点，但没有软件收集器固有的复杂性和开销。