Stochastic Mixed-Signal VLSI Architecture for High-Dimensional Kernel Machines

A mixed-signal paradigm is presented for high-resolution parallel innerproduct computation in very high dimensions, suitable for efficient implementation of kernels in image processing. At the core of the externally digital architecture is a high-density, low-power analog array performing binary-binary partial matrix-vector multiplication. Full digital resolution is maintained even with low-resolution analog-to-digital conversion, owing to random statistics in the analog summation of binary products. A random modulation scheme produces near-Bernoulli statistics even for highly correlated inputs. The approach is validated with real image data, and with experimental results from a CID/DRAM analog array prototype in 0.5

• Type: Conference
• Year: 2001
• Where: NIPS
• Authors: Roman Genov, Gert Cauwenberghs
• Keywords: Analog Array, Analog Array Prototype, Low-power Analog Array, NIPS 2001, NIPS 2007