Isaac Gelado Presents - "GMAC - A Novel Run-Time for CUDA GPUs"
Learn how to use GMAC, a novel run-time for CUDA GPUs. GMAC brings together the host and device memories into a unified virtual address space, enabling the host code to directly access the device memory, and removing the need for data transfers between host and device memories. The GMAC model allows all CPUs in the system to access any memory location, whether such memory location corresponds to the CPU or GPU physical memory. This session will start with the basics of GMAC and move to multi-threaded applications using POSIX threads and I/O operations.
In 2008, he collaborated with Hwu and the Impact Research Group on "CUBA: An Architecture for Efficient CPU/Co-processor Data Communication," for the 22nd ACM International Conference on Supercomputing. Most recently, Isaac presented "GMAC: Global Memory for Accelerators," at the GPU Technology Conference in September.
Isaac holds a Master's degree on Telecommunications Engineering from the Universidad de Valladolid, and a PhD degree from the Universitat Politecnica de Catalunya, where he also held a teaching position in the Computer Architecture Department.