Nowadays, various memory-hungry applications like machine learning algorithms are knocking "the memory wall". Toward this, emerging memories featuring computational capacity are foreseen as a promising solution that performs data process inside the memory itself, so-called computation-in-memory, while eliminating the need for costly data movement. Recent research shows that utilizing the custom extension of RISC-V instruction set architecture to support computation-in-memory operations is effective. To evaluate the applicability of such methods further, this work enhances the standard GNU binary utilities to generate RISC-V executables with Logic-in-Memory (LiM) operations and develop a new gem5 simulation environment, which simulates the entire system (CPU, peripherals, etc.) in a cycle-accurate manner together with a user-defined LiM module integrated into the system. This work provides a modular testbed for the research community to evaluate potential LiM solutions and co-designs between hardware and software.
翻译:如今,各种对内存需求量巨大的应用程序,如机器学习算法,正冲破"内存墙"。为此,具有计算能力的新兴内存被看作是一种很有前途的解决方案,可以在内存本身内执行数据处理,称为内存中计算,同时消除了昂贵的数据移动需求。最近的研究表明,利用自定义RISC-V指令集扩展来支持内存中计算操作是有效的。为了进一步评估这样的方法的适用性,本文增强了标准GNU二进制实用程序,以生成带有逻辑内存(LiM)操作的RISC-V可执行文件,并开发了一个新的gem5仿真环境,该环境以循环准确的方式模拟整个系统(CPU、外设等),并将一个用户定义的LiM模块集成到系统中。本文为研究社区提供了一个模块化测试平台,用于评估可能的LiM解决方案和硬件和软件之间的协同设计。