Message passing on data-parallel architectures
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Debugging GPU stream programs through automatic dataflow recording and visualization
ACM SIGGRAPH Asia 2009 papers
Proceedings of the 1st Workshop on Architectures and Systems for Big Data
RSVM: a region-based software virtual memory for GPU
PACT '13 Proceedings of the 22nd international conference on Parallel architectures and compilation techniques
GPUfs: Integrating a file system with GPUs
ACM Transactions on Computer Systems (TOCS)
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We present GPU-to-CPU callbacks, a new mechanism and abstraction for GPUs that offers them more independence in a heterogeneous computing environment. Specifically, we provide a method for GPUs to issue callback requests to the CPU. These requests serve as a tool for ease-of-use, future proofing of code, and new functionality. We classify the types of these requests into three categories: System calls (e.g. network and file I/O), device/host memory transfers, and CPU compute, and provide motivation as to why all are important. We show how to implement such a mechanism in CUDA using pinned system memory and discuss possible GPU-driver features to alleviate the need for polling, thus making callbacks more efficient with CPU usage and power consumption. We implement several examples demonstrating the use of callbacks for file I/O, network I/O, memory allocation, and debugging.