专利检索 ap:("The Regents of the University of California") AND inv:"Sahand Salamat" 第 1 页

1.

发明申请
CIRCUITS, METHODS, AND ARTICLES OF MANUFACTURE FOR HYPER-DIMENSIONAL COMPUTING SYSTEMS AND RELATED APPLICATIONS 有权

公开(公告)号：US20220019441A1

公开(公告)日：2022-01-20

申请号：US17376105

申请日：2021-07-14

申请人： The Regents of the University of California

发明人： Tajana Simunic Rosing , Justin Morris , Mohsen Imani , Yeseong Kim , John Messerly , Yunhui Guo , Behnam Khaleghi , Saransh Gupta , Sahand Salamat , Joonseop Sim

IPC分类号： G06F9/38 , G06N3/063 , G06F9/30 , G11C13/00

摘要： A hyperdimensional processing system can be configured to process hyperdimensional (HD) data, where the system can include a CPU configured to receive compiled binary executable data including CPU native instructions and hyperdimensional processing unit (HPU) native instructions, wherein the CPU is configured to store the CPU native instructions in a main memory coupled to the CPU for retrieval and execution by the CPU, the CPU further configured to forward the HPU native instructions to a HPU. The HPU can be configured to receive HPU native instructions native instructions and to store the HPU native instructions in a hyperdimensional memory coupled to the HPU for retrieval and execution by the CPU. Other aspects and embodiments according to the present invention are also disclosed herein.

2.

发明申请
METHODS AND SYSTEMS CONFIGURED TO SPECIFY RESOURCES FOR HYPERDIMENSIONAL COMPUTING IMPLEMENTED IN PROGRAMMABLE DEVICES USING A PARAMETERIZED TEMPLATE FOR HYPERDIMENSIONAL COMPUTING 有权

公开(公告)号：US20210334703A1

公开(公告)日：2021-10-28

申请号：US17236640

申请日：2021-04-21

申请人： The Regents of the University of California

发明人： Sahand Salamat , Mohsen Imani , Behnam Khaleghi , Tajana Rosing

IPC分类号： G06N20/00 , G06F15/80

摘要： A method of defining an implementation of circuits in a programmable device can be provided by receiving a plurality of specifications for a hyperdimensional (HD) computing machine learning application for execution on a programmable device, determining parameters for a template architecture for HD computing machine learning using the plurality of specifications, the template architecture including an HD hypervector encoder, an HD associative search unit, programmable device pre-defined processing units, and programmable device pre-defined processing elements within the pre-defined processing units, and generating programmable device code configured to specify resources to be allocated within the programmable device using pre-defined circuits defined for use in the programmable device using the determined parameters for the template architecture.

3.

发明申请
METHODS OF PROVIDING TRAINED HYPERDIMENSIONAL MACHINE LEARNING MODELS HAVING CLASSES WITH REDUCED ELEMENTS AND RELATED COMPUTING SYSTEMS 有权

公开(公告)号：US20210326756A1

公开(公告)日：2021-10-21

申请号：US17224306

申请日：2021-04-07

申请人： The Regents of the University of California

发明人： Behnam Khaleghi , Tajana Simunic Rosing , Mohsen Imani , Sahand Salamat

IPC分类号： G06N20/00 , G06K9/62

摘要： A method of providing a trained machine learning model can include providing a trained non-binary hyperdimensional machine learning model that includes a plurality of trained hypervector classes, wherein each of the trained hypervector classes includes N elements, and then, eliminating selected ones of the N elements from the trained non-binary hyperdimensional machine learning model based on whether the selected element has a similarity with other ones of the N elements, to provide a sparsified trained non-binary hyperdimensional machine learning model.