Simulation Environment with Customized RISC-V Instructions for Logic-in-Memory Architectures

03/21/2023
by   Jia-Hui Su, et al.
0

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.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro