Improving Off-Chip Memory Energy Behavior in a Multi-processor, Multi-bank Environment

  • Victor De La Luz
  • Mahmut Kandemir
  • Ugur Sezer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2624)


Many embedded/portable applications from image and video processing domains are characterized by spending a large fraction of their energy in executing load/store instructions that access off-chip memory. Although most performance-oriented locality optimization techniques reduce the number of memory instructions and, consequently, improve memory energy consumption, we also need to consider energy-oriented approaches if we are to improve energy behavior further.

Our focus in this paper is on a system with multiple homogeneous processors and a multi-bank memory architecture that process large arrays of signals. To reduce energy consumption in such a system, we use a compiler-based approach which exploits low-power operating modes. In such an architecture, one of the major problems is to address the conflicting requirements of maximizing parallelism and reducing energy consumption. This conflict arises because maximizing parallelism requires independent concurrent accesses to different memory banks, whereas reducing energy consumption implies limiting the accesses at a given period of time to a small set of memory banks (so that the remaining banks can be placed into a low-power operating mode). Our approach consists of three complementary steps, namely, parallel access pattern detection, array allocation across memory banks, and data layout transformations. Our preliminary results indicate that our approach leads to significant off-chip memory energy savings without sacrificing the available parallelism.


Reduce Energy Consumption Array Element Access Pattern Memory Bank Memory Controller 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Victor De La Luz
    • 1
  • Mahmut Kandemir
    • 1
  • Ugur Sezer
    • 2
  1. 1.Department of Computer Science and EngineeringPennsylvania State UniversityUniversity Park
  2. 2.Department of Electrical and Computer EngineeringUniversity of Wisconsin-MadisonMadison

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