SIMDRAM：使用DRAM的位串行SIMD处理框架
SIMDRAM: A Framework for Bit-Serial SIMD Processing Using DRAM
摘要：
使用DRAM的处理已经被提出用于有限的一组基本操作（即，逻辑运算、加法）。然而，为了能够完全采用使用DRAM的处理，有必要为更复杂的操作提供支持。在本文中，我们提出了SIMDRAM，一个灵活的通用处理使用DRAM框架，通过使用每个DRAM列作为一个独立的SIMD通道来执行位串行操作，使大范围的操作的并行计算。SIMDRAM由三个关键步骤组成，以实现DRAM中的期望操作：（1）构建期望操作的有效的基于多数的表示，（2）将操作输入和输出操作数映射到DRAM行和产生期望操作的所需DRAM命令，以及（3）执行操作。这三个步骤确保了DRAM中任意复杂操作的高效计算。前两个步骤使用户能够灵活地在DRAM中有效地实现和计算任何所需的操作。第三步对用户透明地控制DRAM内计算的执行流程。我们全面评估SIMDRAM的可靠性，面积开销，操作吞吐量和能源效率使用广泛的操作和七个不同的现实世界的内核，以证明其通用性。我们的研究结果表明，与最先进的DRAM计算机制相比，SIMDRAM提供了高达5.1倍的操作吞吐量和2.5倍的能源效率，以及高达2.5倍的实际内核加速，同时产生不到1%的DRAM芯片面积开销。与CPU和高端GPU相比，SIMDRAM的能效分别提高了257倍和31倍，同时提供了93倍和6倍的操作吞吐量。
英文摘要：
Processing-using-DRAM has been proposed for a limited set of basic operations (i.e., logic operations, addition). However, in order to enable the full adoption of processing-using-DRAM, it is necessary to provide support for more complex operations. In this paper, we propose SIMDRAM, a flexible general-purpose processing-using-DRAM framework that enables massively-parallel computation of a wide range of operations by using each DRAM column as an independent SIMD lane to perform bit-serial operations. SIMDRAM consists of three key steps to enable a desired operation in DRAM: (1) building an efficient majority-based representation of the desired operation, (2) mapping the operation input and output operands to DRAM rows and to the required DRAM commands that produce the desired operation, and (3) executing the operation. These three steps ensure efficient computation of any arbitrary and complex operation in DRAM. The first two steps give users the flexibility to efficiently implement and compute any desired operation in DRAM. The third step controls the execution flow of the in-DRAM computation, transparently from the user. We comprehensively evaluate SIMDRAM's reliability, area overhead, operation throughput, and energy efficiency using a wide range of operations and seven diverse real-world kernels to demonstrate its generality. Our results show that SIMDRAM provides up to 5.1x higher operation throughput and 2.5x higher energy efficiency than a state-of-the-art in-DRAM computing mechanism, and up to 2.5x speedup for real-world kernels while incurring less than 1% DRAM chip area overhead. Compared to a CPU and a high-end GPU, SIMDRAM is 257x and 31x more energy-efficient, while providing 93x and 6x higher operation throughput, respectively.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
