Technology Mapping into General Programmable Cells

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Presentation transcript:

Technology Mapping into General Programmable Cells Alan Mishchenko Robert Brayton Department of EECS, UC Berkeley Wenyi Feng Jonathan Greene Microsemi Corporation, SOC Products Group

Overview Boolean matching is used in synthesis for FPGAs To map into current programmable cells To research future cell architectures Boolean matching methods are often specialized, slow, and require manual effort We propose a new Boolean matcher, which is General (works for many types of cells) Fast (due to the use of concurrency) Automatic (does not require manual tuning) Experiments show it is useful in practice 2

Boolean Matching Given a programmable cell and a Boolean functions, find if a cell can be programmed to implement a given function Programmable cell Function that can be implemented: F = AND(a, b, c, d, e) Function that cannot be implemented: F = XOR(a, b, c, d, e) e a b c d

Small Practical Functions Classifications of Boolean functions Random functions Specialized classes of functions Symmetric, unate, etc Logic synthesis and technology mapping deal with Functions appearing in the designs Functions having small support (up to 16 variables) We call them small practical functions (SPFs) We concentrate on SPFs in this work

The Proposed Matching Flow Pre-computation Collect SPFs appearing in the design(s) Input and pre-process cell description Perform Boolean matching concurrently for all SPFs and save data into a file During mapping Perform additional Boolean matching step Allow only matchable functions to be used

Programmable Cells Used

Area Comparison

Delay and Runtime Comparison

Conclusions Introduced Boolean matching problem Described a mapping flow with matching Experimented with two programmable cells and reviewed the tradeoffs Future work will focus on Improving implementation Extending to standard cells Use in technology-independent synthesis

Abstract Field-Programmable Gate Arrays (FPGA) implement logic functions using programmable cells, such as K-input lookup-tables (K-LUTs). A K-LUT can implement any Boolean function with K inputs and one output. Methods for mapping into K-LUTs are extensively researched and widely used. Recently, cells other than K LUTs have been explored, for example, those composed of several LUTs, and combinations of LUTs and gates. Known methods for mapping into these cells are specialized and complicated, requiring a substantial effort to evaluate such custom cell architectures. This paper presents a general approach to efficiently map into single-output K-input cells containing LUTs, MUXes, and other elementary gates. Cells with K up to 16 inputs can be handled. The mapper is fully automated and takes a logic network and a symbolic description of a programmable cell, and produces an optimized network composed of instances of the given cell. Past work on delay/area optimization during mapping is applicable and leads to good quality of results.