EMPLOYING MULTIPLE CHANNELS FOR DEADLOCK AVOIDANCE IN A CACHE COHERENCY PROTOCOL

Patent №

US 6,014,690

Granted

2000-01-11

Filed 1997

Owner

DIGITAL EQUIPMENT CORPORATION

Lab

AI components

1

hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

08957531

An architecture and coherency protocol for use in a large SMP computer system includes a hierarchical switch structure which allows for a number of multi-processor nodes to be coupled to the switch to operate at an optimum performance. Within each multi-processor node, a simultaneous buffering system is provided that allows all of the processors of the multi-processor node to operate at peak performance. A memory is shared among the nodes, with a portion of the memory resident at each of the multi-processor nodes. Each of the multi-processor nodes includes a number of elements for maintaining memory coherency, including a victim cache, a directory and a transaction tracking table. The victim cache allows for selective updates of victim data destined for memory stored at a remote multi-processing node, thereby improving the overall performance of memory. Memory performance is additionally improved by including, at each memory, a delayed write buffer which is used in conjunction with the directory to identify victims that are to be written to memory. An arb bus coupled to the output of the directory of each node provides a central ordering point for all messages that are transferred through the SMP. The messages comprise a number of transactions, and each transaction is assigned to a number of different virtual channels, depending upon the processing stage of the message. The use of virtual channels thus helps to maintain data coherency by providing a straightforward method for maintaining system order. Using the virtual channels and the directory structure, cache coherency problems that would previously result in deadlock may be avoided.

AI hardwareG06F 12/0828G06F 12/0813G06F 12/0817

AI classification

AI hardware0.77
Vision0.04
Planning0.00
Evolutionary computation0.00
Natural language0.00
Speech0.00
Machine learning0.00
Knowledge representation0.00

Ownership

DIGITAL EQUIPMENT CORPORATION

assignment · 87980944

Assignors

SHARMA, MADHUMITRA, VAN DOREN, STEPHEN R., STEELY, JR., SIMON C.

On an employer assignment, the assignors are typically the inventors.

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