Mixed torus and hypercube multi-rank tensor expansion method
AssigneeShanghai Redneurons Co., Ltd
InventorsYuefan Deng, Peng Zhang
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Abstract
The present invention provides a mixed torus and hypercube multi-rank tensor expansion method which can be applied to the communication subsystem of a parallel processing system. The said expansion method is based on the conventional torus and hypercube topologies. A mixed torus and hypercube multi-rank tensor expansion interconnection network is built up by means of supernodes equipped with expansion interfaces. This method not only provides more bisection bandwidth to the entire system but also improves the long-range communication and global operations. Affirmatively, this expansion method can achieve better scalability and flexibility for the parallel system for a given system size.
Claims16
A method for expansion of a cube, integrated with supernodes, each supernode being provided with expansion interfaces into a larger-scale parallel processing system, said method comprising:
- providing the cube as a mix of hypercube and torus topologies;
- expanding the cube via multi-rank tensor expansion;
- providing each of the supernodes, respectively, with a plurality of processing nodes and Axon nodes, wherein the Axon nodes connect a subgroup of or all of the plurality of processing nodes for a respective supernode;
- interconnecting the plurality of processing nodes of the respective supernode as a multi-dimensional torus to form an internal interconnection network, wherein the internal interconnection network handles internal communication between the plurality of processing nodes;
- interconnecting the Axon nodes to form an external interconnection network, wherein the external interconnection network handles external communication between the supernodes.
A method for expansion of a cube, integrated with supernodes, each supernode being provided with expansion interfaces into a large-scale parallel processing system, said method comprising:
- providing the cube as a mix of hypercube and torus topologies;
- expanding the cube via multi-rank tensor expansion;
- interconnecting processing nodes in all of the supernodes as a multidimensional torus to form a trunk interconnection network, responsible for communication between the processing nodes;
- adding one or more Axon nodes to each supernode, wherein the one or more Axon nodes connect a subgroup of processing nodes of the respective supernode and provides external interfaces;
- and
- interconnecting all of the external interfaces as a multi-dimensional torus to form an external interconnection network, wherein the external interconnection handles external communication between the supernodes.
Dependencies are inferred from the claim text.