Who We Are

Based in San Diego, California, EP Analytics was founded by leading researchers in the performance analysis, modeling and characterization of high performance computing (HPC) systems.

“Maximizing the effectiveness and energy-efficiency of existing systems based on specific application characteristics.”

The company assists clients in the government and private sector in designing and procuring mission-critical HPC systems and maximizing the effectiveness and energy-efficiency of existing systems based on specific application characteristics. With the increasing reliance on modeling & simulation, virtual prototyping, and computer-aided engineering across numerous market segments, EP Analytics' expertise and tools can assist enterprises in maximizing the return-on-investment in HPC systems. The company's team has expertise in x86, Power, and ARM processor architectures, parallel computing, program inspection and analysis, hardware-software co-design, performance characterization, and other areas. Current government clients include the Department of Defense, Department of Energy, and NASA.

Laura Carrington, Ph.D.

Co-founder and Vice President of Research

Dr. Carrington is an expert in High Performance Computing with over 50 publications in HPC benchmarking, workload analysis, application performance analysis and optimization, analysis of accelerators (i.e. FPGAs and GPUs) for scientific workloads, tools in performance analysis (i.e. processor and network simulators), and energy-efficient computing. She has presented at numerous invited talks, is a member of various panels and committees, and has been a member of the DoD HPCMP Performance team involved in their annual HPC system procurement for over 10 years.

Ron Hawkins

Co-founder and President

Ron Hawkins' experience spans nearly thirty years in fields including high performance computing, consumer electronics, mission-critical defense/industrial electronics, and telecommunications. Ron held VP-level positions at the Sony Corporation of America, Sony Electronics and the Titan Corporation, managing business units in consumer and defense/industrial electronics. Most recently, Ron has been the director of industry relations at the San Diego Supercomputer Center, an organized research unit of the University of California, San Diego, where Ron set up industrial and academic collaborations in next generation sequencing, hybrid computing research, cloud storage systems, and other areas.

Ron's technology background and interests include high performance and cloud computing, data-intensive systems, microelectronics, embedded and real-time systems, and systems engineering/integration. Some of Ron's notable accomplishments include managing the launch of a new mobile consumer electronics device, developing overall system designs for one of the pioneering ventures in video-on-demand, implementing real-time video/imaging products based on FPGA computing technology, and advising the Department of Defense on large-scale, distributed computing systems.

Ron received the Master of Information Systems degree from Virginia Tech, the BSEE degree from the U.S. Naval Academy, and has recently taken courses in data mining from the UC San Diego extension.

Allyson Cauble-Chantrenne

Software Engineer

Allyson recently graduated with her M.S. in Computer Science from the University of California, San Diego. She was fortunate enough to be introduced to the world of High Performance Computing during an internship at Lawrence Livermore National Lab, where she spent a summer working on a performance analysis tool. She is excited to continue working in the field as a software engineer at EP Analytics. When she's not working, she can be seen swing dancing at various events in Southern California.

Ananta Tiwari, Ph.D.

Director of Research Operations

Ananta is an expert in performance, power and energy modeling and in model- and empirically-driven application tuning and optimization. His research interests include developing analytical and statistical models for the energy consumption of large-scale data-intensive applications and utilizing those models as the basis for developing application- and energy-aware auto-tuning techniques for HPC applications.

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