Presentation

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Exploring Fine-Grained Memory Analysis for PIM Offloading

SessionResearch, ACM SRC, and Doctoral Showcase Posters

DescriptionIn modern computing, a challenge is the data bottleneck between the CPU and RAM. This issue arises because the CPU can process data faster than it can be accessed from RAM; this is worsened by the fact that large amounts of RAM are less accessible than a powerful CPU. Furthermore, RAM’s high cost creates a need for a cost-effective solution. Processing in Memory (PIM) offers a potential remedy by reducing data movement, thus alleviating bottlenecks. To optimize the use of this new hardware, developers need to identify when to offload their programs to a PIM device. To address this need, we have developed a solution that enables developers to run Python programs through our pipeline, highlighting the memory-intensive parts of their code.

Authors

Thomas Papka

Loyola University, Chicago

Nanda Velugoti

Illinois Institute of Technology

Kyle Hale

Illinois Institute of Technology