Approximator: A Software Tool for Automatic Generation of Approximate Arithmetic Circuits

A software tool for automatic generation of neural hardware

Natural neural networks greatly benefit from their parallel structure that makes them fault tolerant and fast in processing the inputs. Their artificial counterpart, artificial neural networks, proved difficult to implement in hardware where they could have a similar structure. Although, many circuits have been developed, they usually present problems regarding accuracy, are application specifi...

Design of Energy - Efficient Approximate Arithmetic Circuits

Approximate Inference by Compilation to Arithmetic Circuits

Arithmetic circuits (ACs) exploit context-specific independence and determinism to allow exact inference even in networks with high treewidth. In this paper, we introduce the first ever approximate inference methods using ACs, for domains where exact inference remains intractable. We propose and evaluate a variety of techniques based on exact compilation, forward sampling, AC structure learning...

A Tool for Automatic Test Plan Generation For Mixed-Signal Circuits

| In this paper, a tool for the automatic test plan generation for mixed-signal circuits is described. It is used during the design and test tra-ject of a mixed-signal circuit. The functional hierarchy of the analogue parts and the data present in the design database are used for test selection. The reuse of design and test data has been made possible by means of a library-based approach. Resul...

Automatic Test Pattern Generation for Digital Circuits

Digital circuits complexity and density are increasing and at the same time it should have more quality and reliability. It leads with high test costs and makes the validation more complex. The main aim is to develop a complete behavioral fault simulation and automatic test pattern generation (ATPG) system for digital circuits modeled in verilog and VHDL. An integrated Automatic Test Generation...