arXiv · cs.AI · Mehdi Safarpour · 9 小时前模型评分38
一种面向信号处理与深度神经网络推理的跨域矩阵引擎
A Cross-Domain Matrix Engine for Signal Processing and Deep Neural Net Inference
导读
研究提出一种可在脉动阵列（SA，Systolic Array）与张量式结构间按操作重配置的矩阵引擎，用多路选择器复用阵列内乘累加单元和寄存器，同时构建空间归约加法树与时间归约累加器。
分类置信度
中 · 待人工复核
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
事件类型：研究发布
证据摘录
- “We propose a single engine that operates primarily as a SA and, through low-cost reconfiguration, transforms into a tensor-style engine on a per-operation basis.”
- “SCALE-Sim simulations shows up to 7.5x lower latency for small complex value PHY kernels.”
- “Even on DNN workloads, it achieves up to 1.65x speedups over vanilla SA execution with trivial increase of memory accesses, retaining the systolic array's memory access advantage.”
- “Synthesis results estimate reconfigurable fabric costs only 8% power and 13.6% area overheads.”
来源：arXiv · cs.AI · arxiv.org