Nooshin Mirzadeh


Near-Data Processing

  Computer Engineering Department, Floor 1, Class 101
  Thursday, 31 December 2015
  15:00 - 16:00


Computing in large-scale systems is shifting away from the traditional compute-centric model successfully used for many decades into one that is much more data-centric. This transition is driven by the evolving nature of what computing comprises, no longer dominated by the execution of arithmetic and logic calculations but instead becoming dominated by large data volume and the cost of moving data to the locations where computations are performed. Data movement impacts performance, power efficiency and reliability, three fundamental components of a system. These trends are leading to changes in the computing paradigm, in particular the notion of moving computation to the data in a so-called Near-Data Processing approach, which seeks to perform computations in the most appropriate location depending on where data resides and what needs to be extracted from that data. Thus, in NDP, computation can be performed right at the data’s home, either in caches, main memory, or persistent storage. This is in contrast to the movement of data toward a CPU independent of where it resides, as is done traditionally.

In this talk, we specifically look at near-memory processing. Data movement between memory and CPU is a well-known energy bottleneck for analytics. Near-Memory Processing (NMP) is a promising approach for eliminating this bottleneck by shifting the bulk of the computation toward memory arrays in emerging stacked DRAM chips.


Nooshin Mirzadeh is a student at Computer Sciences, École Polytechnique Fédérale de Lausanne (EPFL). She has been working in the Parallel Systems Architecture (PARSA) group, which advised by Prof. Babak Falsafi, since Sept. 2013. Her research interest lies in computer architecture, especially in high performance energy-efficient memory systems including 3D integration, and near-memory processing.