A Workload and Programming Ease Driven Perspective of Processing-in-Memory

26 Jul 2019Saugata GhoseAmirali BoroumandJeremie S. KimJuan Gómez-LunaOnur Mutlu

Many modern and emerging applications must process increasingly large volumes of data. Unfortunately, prevalent computing paradigms are not designed to efficiently handle such large-scale data: the energy and performance costs to move this data between the memory subsystem and the CPU now dominate the total costs of computation... (read more)

PDF Abstract


No code implementations yet. Submit your code now


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper

🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet