Hardware Acceleration of High-Performance Computational Flow Dynamics Using High-Bandwidth Memory-Enabled Field-Programmable Gate Arrays

Scientific computing is at the core of many High-Performance Computing applications, including computational flow dynamics. Because of the utmost importance to simulate increasingly larger computational models, hardware acceleration is receiving increased attention due to its potential to maximize the performance of scientific computing. Field-Programmable Gate Arrays could accelerate scientific computing because of the possibility to fully customize the memory hierarchy important in irregular applications such as iterative linear solvers. In this article, we study the potential of using Field-Programmable Gate Arrays in High-Performance Computing because of the rapid advances in reconfigurable hardware, such as the increase in on-chip memory size, increasing number of logic cells, and the integration of High-Bandwidth Memories on board. To perform this study, we propose a novel Sparse Matrix-Vector multiplication unit and an ILU0 preconditioner tightly integrated with a BiCGStab solver kernel. We integrate the developed preconditioned iterative solver in Flow from the Open Porous Media project, a state-of-the-art open source reservoir simulator. Finally, we perform a thorough evaluation of the FPGA solver kernel in both stand-alone mode and integrated in the reservoir simulator, using the NORNE field, a real-world case reservoir model using a grid with more than 10 5 cells and using three unknowns per cell.

FPGAs in The Cloud

As cloud computing grows, the types of computational hardware available in the cloud are diversifying. Field Programmable Gate Arrays (FPGAs) are a relatively new addition to high-performance computing in the cloud, with the ability to accelerate a range of different applications, and the flexibility to offer different cloud computing models. A new and growing configuration is to have the FPGAs directly connected to the network and thus reduce the latency in delivering data to processing elements. We survey the state-of-the-art in FPGAs in the cloud and present the Open Cloud Testbed (OCT), a testbed for research and experimentation into new cloud platforms, which includes network-attached FPGAs in the cloud.