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His paper proposes that all data elements in a computer memory be made to be self-identifying by means of a tag. The paper shows that the advantages of the change from the traditional von Neumann machine to tagged architecture are seen in all software areas including programming systems, operating systems, debugging systems, and systems of software instrumentation. It discusses the advantages that accrue to the hardware designer in the implementation and gives examples for large- and small-scale systems.

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The economic costs of such an implementation for a minicomputer system are examined. The paper concludes that such a machine architecture may well be a suitable replacement for the traditional von Neumann architecture.
It is interesting to see that rivals NVIDIA and ATI are both creating the tools and provide support such that their wonderful hardware can be easily used as a math coprocessor for highly demanding scientific computating. I remember it was no more than 8 years ago when people were starting to exploit graphics accelerators to compute general functions by abusing the OpenGL API. If you wanted to do something really interesting those days you would need access to an SGI graphics workstation or higher.

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Today you can get similar if not better performance with consumer level graphics cards and the interfaces for programming them are far better especially with the introduction of such kits as CUDA.

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The runtime continually monitors and adapts to the state and utilization of its computing resources, as well as the information needs expressed by the users, and availability of data to meet those needs.