Issue No. 02 - July-Dec. (2018 vol. 17)
Soroosh Khoram , Department of Electrical and Computer Engineering, University of Wisconsin - Madison, Madison, WI
Yue Zha , Department of Electrical and Computer Engineering, University of Wisconsin - Madison, Madison, WI
Jing Li , Department of Electrical and Computer Engineering, University of Wisconsin - Madison, Madison, WI
Associative Processing (AP) is a promising alternative to the Von Neumann model as it addresses the memory wall problem through its inherent in-memory computations. However, because of the countless design parameter choices, comparisons between implementations of two so radically different models are challenging for simulation-based methods. To tackle these challenges, we develop an alternative analytical approach based on a new concept called architecturally-determined complexity. Using this method, we asymptotically evaluate the runtime/storage/energy bounds of the two models, i.e., AP and Von Neumann. We further apply the method to gain more insights into the performance bottlenecks of traditional AP and develop a new machine model named Two Dimensional AP to address these limitations. Finally, we experimentally validate our analytical method and confirm that the simulation results match our theoretical projections.
Computational modeling, Complexity theory, Two dimensional displays, Runtime, Analytical models, Parallel processing, Computer architecture
S. Khoram, Y. Zha and J. Li, "An Alternative Analytical Approach to Associative Processing," in IEEE Computer Architecture Letters, vol. 17, no. 2, pp. 113-116, 2018.