Implementing a Multicore System Resource Manager Using an Industry-Standard API

Presented April 6, 2011



Multicore processors designed for embedded applications can consist of a varying number of shared system resources, such as cores, hardware accelerators and memory. Furthermore, you can expect that these resources will change over time and require you to scale your application to allow for the inevitable evolution. This webinar will demonstrate how to utilize the industry-standard Multicore Resource Management API (MRAPI(TM)) to build dynamic scalability and portability into your applications. The webinar will provide a brief introduction to MRAPI, discuss how to utilize the example implementation provided by the Multicore Association, and explain how MRAPI can be used in conjunction with MCAPI to handle many of the functions of a multicore system.


Although it's not required, we recommend that you review our previous webinar called "Designing an Industry Standard API to Manage Multicore System Resources"


Jim Holt - Manager of Processor Core Architecture and Modeling Team, Freescale and MRAPI working group chair

Jim Holt leads the Processor Core Architecture and Modeling Team for Freescale's Networking and Multimedia group, and is a Research Scientist for the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Jim has 27 years of industry experience focused on microprocessor and SoC architecture, distributed systems, design verification, and optimization. Jim is an IEEE Senior Member, is a member of the Industrial Advisory Board for the Department of Computer Science at Texas State University, and is a board member for the Multicore Association. He is also chair of the Integrated Systems & Circuits Science area for the Semiconductor Research Corporation (SRC), and chair of the Multicore Resource API Working group for the Multicore Association. Jim has over 30 refereed publications in journals and conferences, frequently serves on research proposal selection committees, and on program committees for peer reviewed journals and conferences. Jim earned a Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin, and an MS in Computer Science from Texas State University.