Mozilla Corporation since Feb 2010
Compiler Engineer
NVIDIA Aug 2008 - Mar 2010
Software/Hardware Engineer
Cornell University Fusion Research Group Mar 2007 - Mar 2008
Undergraduate Research Student
NVIDIA May 2007 - Aug 2007
ASIC Design Intern
Cornell University ACCEL Computing Laboratory Oct 2005 - Mar 2007
Senior Technical Consultant
Education:
Cornell University 2004 - 2008
B.S., Electrical and Computer Engineering, Computer ScienceDouble major with degree specialization in Microprocessor Architecture within Electrical and Computer Engineering.
Relevant Coursework: High Performance Microprocessor Architecture, Algorithm Design and Analysis, Operating Systems, Computer Networking, Information Retrieval, Scientific Computation, Microcontroller Design, Functional Programming and Data Structures
Independent Projects: Way-predictive selective direct-mapping cache performance analysis through binary instrumentation, asynchronous I/O webcrawler using Python's "Twisted" framework, USB library for 16MHz 8-bit AVR microcontroller, automated university break comparison engine
Medical School Creighton University School of Medicine Graduated: 1993
Languages:
English Spanish
Description:
Dr. Leary graduated from the Creighton University School of Medicine in 1993. He works in Bristol, CT and specializes in Diagnostic Radiology. Dr. Leary is affiliated with Bristol Hospital.
- Mountain View CA, US Rahul Nagarajan - Sunnyvale CA, US Dong Hyuk Woo - San Jose CA, US Christopher Daniel Leary - Sunnyvale CA, US
International Classification:
G06F 17/16 G06F 17/14
Abstract:
Methods, systems, and apparatus, including a system for transforming sparse elements to a dense matrix. The system is configured to receive a request for an output matrix based on sparse elements including sparse elements associated with a first dense matrix and sparse elements associated with a second dense matrix; obtain the sparse elements associated with the first dense matrix fetched by a first group of sparse element access units; obtain the sparse elements associated with the second dense matrix fetched by a second group of sparse element access units; and transform the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix to generate the output dense matrix that includes the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix.
- Mountain View CA, US Rahul Nagarajan - Sunnyvale CA, US Dong Hyuk Woo - San Jose CA, US Christopher Daniel Leary - Sunnyvale CA, US
International Classification:
G06F 17/16 G06F 17/14
Abstract:
Methods, systems, and apparatus, including a system for transforming sparse elements to a dense matrix. The system is configured to receive a request for an output matrix based on sparse elements including sparse elements associated with a first dense matrix and sparse elements associated with a second dense matrix; obtain the sparse elements associated with the first dense matrix fetched by a first group of sparse element access units; obtain the sparse elements associated with the second dense matrix fetched by a second group of sparse element access units; and transform the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix to generate the output dense matrix that includes the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix.
- Mountain View CA, US Rahul Nagarajan - Sunnyvale CA, US Dong Hyuk Woo - San Jose CA, US Christopher Daniel Leary - Sunnyvale CA, US
International Classification:
G06F 17/16 G06F 17/14
Abstract:
Methods, systems, and apparatus, including a system for transforming sparse elements to a dense matrix. The system is configured to receive a request for an output matrix based on sparse elements including sparse elements associated with a first dense matrix and sparse elements associated with a second dense matrix; obtain the sparse elements associated with the first dense matrix fetched by a first group of sparse element access units; obtain the sparse elements associated with the second dense matrix fetched by a second group of sparse element access units; and transform the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix to generate the output dense matrix that includes the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix.
Executing Computational Graphs On Graphics Processing Units
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a data entity that causes a processing unit to process a computational graph. In one aspect, a method includes the actions of receiving data identifying a computational graph, the computational graph including a plurality of nodes representing operations; obtaining compilation artifacts for processing the computational graph on a processing unit; and generating a data entity from the compilation artifacts, wherein the data entity, when invoked, causes the processing unit to process the computational graph by executing the operations represented by the plurality of nodes.
Executing Computational Graphs On Graphics Processing Units
- Mountain View CA, US Christopher Daniel Leary - Sunnyvale CA, US
Assignee:
Google Inc. - Mountain View CA
International Classification:
G06T 1/20 G06N 3/08
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a data entity that causes a processing unit to process a computational graph. In one aspect, method includes the actions of receiving data identifying a computational graph, the computational graph including a plurality of nodes representing operations; obtaining compilation artifacts for processing the computational graph on a processing unit; and generating a data entity from the compilation artifacts, wherein the data entity, when invoked, causes the processing unit to process the computational graph by executing the operations represented by the plurality of nodes.
- Mountain View CA, US Rahul Nagarajan - Sunnyvale CA, US Dong Hyuk Woo - San Jose CA, US Christopher Daniel Leary - Mountain View CA, US
International Classification:
G06F 17/16 G06F 17/14
Abstract:
Methods, systems, and apparatus, including a system for transforming sparse elements to a dense matrix. The system is configured to receive a request for an output matrix based on sparse elements including sparse elements associated with a first dense matrix and sparse elements associated with a second dense matrix; obtain the sparse elements associated with the first dense matrix fetched by a first group of sparse element access units; obtain the sparse elements associated with the second dense matrix fetched by a second group of sparse element access units; and transform the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix to generate the output dense matrix that includes the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix.
- Mountain View CA, US Rahul Nagarajan - Sunnyvale CA, US Dong Hyuk Woo - San Jose CA, US Christopher Daniel Leary - Mountain View CA, US
International Classification:
G06F 17/16 G06F 17/14
Abstract:
Methods, systems, and apparatus, including a system for transforming sparse elements to a dense matrix. The system is configured to receive a request for an output matrix based on sparse elements including sparse elements associated with a first dense matrix and sparse elements associated with a second dense matrix; obtain the sparse elements associated with the first dense matrix fetched by a first group of sparse element access units; obtain the sparse elements associated with the second dense matrix fetched by a second group of sparse element access units; and transform the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix to generate the output dense matrix that includes the sparse elements associated with the first dense matrix and the sparse elements associated with the second dense matrix.
- Mountain View CA, US Rahul Nagarajan - Sunnyvale CA, US Dong Hyuk Woo - San Jose CA, US Christopher Daniel Leary - Mountain View CA, US
International Classification:
G06F 17/16 H03M 7/30 G06F 17/14
Abstract:
Methods, systems, and apparatus, including a system for transforming sparse elements into a dense matrix. The system includes a data fetch unit that includes a plurality of processors, the data fetch unit configured to determine, based on identifications of the subset of the particular sparse elements, a processor designation for fetching the subset of the particular sparse elements. The system includes a concatenation unit configured to generate an output dense matrix based on a transformation that is applied to the sparse elements fetched by the data fetch unit.
Pharmacists Gene Svirskiy, 33, of Ashland, Joseph Evanosky, 42, of Westford, and Christopher Leary, 30, of Shrewsbury, and pharmacy technician Scott Connolly, 42, of East Greenwich, R.I., who were all charged with racketeering, racketeering conspiracy and multiple counts of mail fraud. Some faced ad