Spatial-lattice computations with finite-range interactions are an important class of easily parallelized computations. This class includes many simple and direct algorithms for physical simulation, virtual-reality simulation, agent-based modeling, logic simulation, 2D and 3D image processing and rendering, and other volumetric data processing tasks. The range of applicability of such algorithms is completely dependant upon the lattice-sizes and processing speeds that are computationally feasible. Using embedded DRAM and a new technique for organizing SIMD memory and communications we can efficiently utilize 1 Tbit/sec of sustained memory bandwidth in each chip in an indefinitely scalable array of chips. This allows a 10,000-fold speedup per memory chip for these algorithms compared to the CAM-8 lattice gas computer, and is about one million times faster per memory chip for these calculations than a CM-2.

We propose an FPGA chip architecture based on a conventional FPGA logic array core, in which I/O pins are clocked at a much higher rate than that of the logic array that they serve. Wide data paths within the chip are time multiplexed at the edge of the chip into much faster and narrower data paths that run off-chip. This kind of arrangement makes it possible to interface a relatively slow FPGA core with high speed memories and data streams, and is useful for many pin-limited FPGA applications. For efficient use of the highest bandwidth DRAMs, our proposed chip includes a RAMBUS DRAM interface, a burst-transfer controller, and burst buffers. This proposal is motivated by our work with virtual processor cellular automata (CA) machines-a kind of SIMD computer. Our next generation of CA machines requires reconfigurable FPGA-like processors coupled to the highest speed DRAMs and SRAMs available. Unfortunately, no current FPGA chips have appropriate DRAM I/O support or the speed needed to easily interface with pipelined SRAMs. The chips proposed would make a wide range of large-scale CA simulations of 3D physical systems practical and economical-simulations that are currently well beyond the reach of any existing computer. These chips would also be well suited to a broad range of other simulation, graphics and DSP-like applications.