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John Michael Melonakos, 44Atlanta, GA

John Melonakos Phones & Addresses

Atlanta, GA   

525 Brook Cir, Roswell, GA 30075   

413 S State St, Provo, UT 84606   

1976 110 W, Provo, UT 84604   

585 400 E, Provo, UT 84606   

4199 Alaina Cir, Austell, GA 30106   

Latham, NY   

Smyrna, GA   

Newton, NC   

Mentions for John Michael Melonakos

John Melonakos resumes & CV records

Resumes

John Melonakos Photo 11

Chief Executive Officer And Co-Founder

Location:
3423 Piedmont Rd northeast, Atlanta, GA 30305
Industry:
Computer Software
Work:
AccelerEyes since 2007
CEO & Co-Founder
Georgia Institute of Technology 2004 - 2008
Research Assistant
Education:
Georgia Institute of Technology 2004 - 2008
PhD, ECE
Brigham Young University 1998 - 2004
BS, EE
Skills:
Algorithms, High Performance Computing, Computer Vision, Image Processing, C++, Start Ups, Cuda, Signal Processing, Machine Learning, Parallel Computing, C, Medical Imaging, Software Engineering, Linux, Computer Science, Software Development, Research, Programming, Marketing, Matlab, Python, Computer Architecture, Sales, Embedded Systems, Gpu, Artificial Intelligence, Digital Signal Processors, Software Design, Optimization, Latex, Distributed Systems, Compilers, Pattern Recognition, Opengl, Multithreading, Emacs, Perl, Parallel Programming, Algorithm Design, Digital Image Processing, Scalability, Fortran, Android, Bash, Neural Networks, Gpgpu, Opencv, Qt
Languages:
Spanish
John Melonakos Photo 12

President

Location:
1222 Hollywood Dr, Monroe, MI 48162
Industry:
Medical Practice
Work:
Pvp
President

Publications & IP owners

Us Patents

System For Improving Utilization Of Gpu Resources

US Patent:
2009014, Jun 4, 2009
Filed:
Nov 26, 2008
Appl. No.:
12/323572
Inventors:
Gallagher Pryor - Atlanta GA, US
James G. Malcolm - Marietta GA, US
John Melonakos - Austell GA, US
Tauseef ur Rehman - Atlanta GA, US
Assignee:
ACCELEREYES, LLC - Austell GA
International Classification:
G06T 1/20
US Classification:
345522
Abstract:
A method, executable on a digital computer that includes a central processing unit (CPU) and a graphics processing unit (GPU), executes a series of instructions, in which a GPU data type is defined and at least one data unit is designated with the GPU data type. A series of instructions is executed on the central processing unit. The method determines that a first unit of instruction code, included in the series of instructions, will be scheduled to operate on a GPU data type-designated data unit within a predetermined number of cycles. The GPU data type-designated data unit is caused to be operated on by a second unit of instruction code, that functionally corresponds to the first unit of instruction code. The second unit of instruction code is executed on the graphics processing unit.

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