We propose resource discovery and load balancing techniques to accommodate computing nodes with many types of computing elements, such as multi-core CPUs and GPUs, in a peer-to-peer desktop grid architecture. Heterogeneous nodes can have multiple types of computing elements, and the performance and characteristics of each computing element can be very different. Our scheme takes into account these diverse aspects of heterogeneous nodes to maximize overall system throughput. However, straightforward methods of handling diverse computing elements that differ on many axes can result in high overheads, both in local state and in communication volume. We describe approaches that minimize messaging costs without sacrificing the failure resilience provided by an underlying peer-to-peer overlay network. Simulation results show that our scheme's load balancing performance is comparable to that of a centralized approach, that communication costs are reduced significantly compared to the existing system, and that failure resilience is not compromised.
['Jaehwan Lee', 'Peter J. Keleher', 'Alan Sussman']
Supporting Computing Element Heterogeneity in P2P Grids