A Framework for Safe Execution of User-Uploaded Algorithms
Toni Tan, René Weller, Gabriel Zachmann · 2022
In recent years, a trend has existed for an open benchmark aiming for reproducible and comparable benchmarking results. The best reproducibility can be achieved when performing the benchmarks in the same hard- and software environment. This can be offered as a web service. One challenge of such a web service is the integration of new algorithms into the existing benchmarking tool due to security concerns. In this paper, we present a framework that allows the safe execution of user-uploaded algorithms in such a benchmark-as-a-service web tool. To guarantee security as well as reproducibility and comparability of the service, we extend an existing system architecture to allow the execution of user-uploaded algorithms in a virtualization environment. Our results show that although the results from the virtualization environment are slightly slower by around 3.7% to 4.7% compared with the native environment, the results are consistent across all scenarios with different algorithms, object shapes, and object complexity. Moreover, we have automated the entire process from turning on/off a virtual machine, starting benchmark with intended parameters to communicating with the backend server when the benchmark has finished. Our implementation is based on Microsoft Hyper-V that allows us to benchmark algorithms that use Single Instruction, Multiple Data (SIMD) instruction sets as well as access to the Graphics Processing Unit (GPU).