Reconfigurable computing is a computer architecture combining some of the flexibility of software with the high performance of hardware by processing with very flexible high speed computing fabrics like field-programmable gate arrays (FPGAs). The principal difference when compared to using ordinary microprocessors is the ability to make substantial changes to the datapath itself in addition to the control flow. On the other hand, the main difference with custom hardware, i.e. application-specific integrated circuits (ASICs) is the possibility to adapt the hardware during runtime by "loading" a new circuit on the reconfigurable fabric.
The concept of reconfigurable computing has existed since the 1960s, when Gerald Estrin's paper proposed the concept of a computer made of a standard processor and an array of "reconfigurable" hardware. The main processor would control the behavior of the reconfigurable hardware. The latter would then be tailored to perform a specific task, such as image processing or pattern matching, as quickly as a dedicated piece of hardware. Once the task was done, the hardware could be adjusted to do some other task. This resulted in a hybrid computer structure combining the flexibility of software with the speed of hardware.
In the 1980s and 1990s there was a renaissance in this area of research with many proposed reconfigurable architectures developed in industry and academia, such as: Copacobana, Matrix, , Elixent, NGEN, Polyp, MereGen, PACT XPP, Silicon Hive, Montium, Pleiades, Morphosys, and PiCoGA. Such designs were feasible due to the constant progress of silicon technology that let complex designs be implemented on one chip. Some of the these massively parallel reconfigurable computers were built primarily for special subdomains such as molecular evolution, neural or image processing. The world's first commercial reconfigurable computer, the Algotronix CHS2X4, was completed in 1991. It was not a commercial success, but was promising enough that Xilinx (the inventor of the Field-Programmable Gate Array, FPGA) bought the technology and hired the Algotronix staff. Later machines enabled first demonstrations of scientific principles, such as the spontaneous spatial self-organisation of genetic coding with MereGen.
The fundamental model of the reconfigurable computing machine paradigm, the data-stream-based anti machine is well illustrated by the differences to other machine paradigms that were introduced earlier, as shown by Nick Tredennick's following classification scheme of computing paradigms (see "Table 1: Nick Tredennick’s Paradigm Classification Scheme").