论文标题
TDO-CIM：计算中内存的透明检测和卸载
TDO-CIM: Transparent Detection and Offloading for Computation In-memory
论文作者
论文摘要
计算中内存是一种有希望的非VON Neumann方法，旨在完全减少对内存子系统的数据传输。尽管已经提出了许多架构，但对此类架构的编译器支持仍在落后。在本文中，我们通过提出基于LLVM编译器基础架构的内存计算的端到端编译流来缩小此差距。从顺序代码开始，我们的方法自动检测适合内存加速度的内核。我们在PolyBench/C-Benchmark套件上演示了我们的编译器工具流，并通过将其与最先进的von Neumann架构进行比较，评估了GEM5中提出的内存中架构的好处。
Computation in-memory is a promising non-von Neumann approach aiming at completely diminishing the data transfer to and from the memory subsystem. Although a lot of architectures have been proposed, compiler support for such architectures is still lagging behind. In this paper, we close this gap by proposing an end-to-end compilation flow for in-memory computing based on the LLVM compiler infrastructure. Starting from sequential code, our approach automatically detects, optimizes, and offloads kernels suitable for in-memory acceleration. We demonstrate our compiler tool-flow on the PolyBench/C benchmark suite and evaluate the benefits of our proposed in-memory architecture simulated in Gem5 by comparing it with a state-of-the-art von Neumann architecture.
