Lesley Northam
HORT: a High-Performance MapReduce Framework for Ray Tracing in the Cloud
Lesley Northam, Rob Smits, and Khuzaima Daudjee
Abstract
Ray tracing is a type of high-quality computergenerated
imagery rendering that makes heavy demands on computing
resources. We present a new high-performance ray tracing
framework for cloud computing, allowing computing resources to
be dynamically provisioned within an existing infrastructure on
a pay-per-use basis. Our framework, called HORT, utilizes the
MapReduce programming paradigm, which subdivides tasks that
can be computed in parallel. HORT is easily scaled to any cloud
infrastructure-as-a-service configuration while providing faulttolerance
intrinsically. Importantly, our framework is effective
and efficient in handling large scenes by eliminating the performance
overheads associated with replicating data and on-demand
data requests that are required of other ray tracing frameworks
that employ distribution and parallelism. We demonstrate that
HORT can also utilize efficiently the parallelism of GPUs with
MapReduce in the cloud to offer high-performance.
Papers
Submission in progress.A SIGGRAPH poster regarding HORT was presented in 2011.