FOS: A Modular FPGA Operating System for Dynamic Workloads

With FPGAs now being deployed in the cloud and at the edge, there is a need for scalable design methods which can incorporate the heterogeneity present in the hardware and software components of FPGA systems. Moreover, these FPGA systems need to be maintainable and adaptable to changing workloads while improving accessibility for the application developers. However, current FPGA systems fail to achieve modularity and support for multi-tenancy due to dependencies between system components and lack of standardised abstraction layers. To solve this, we introduce a modular FPGA operating system -- FOS, which adopts a modular FPGA development flow to allow each system component to be changed and be agnostic to the heterogeneity of EDA tool versions, hardware and software layers. Further, to dynamically maximise the utilisation transparently from the users, FOS employs resource-elastic scheduling to arbitrate the FPGA resources in both time and spatial domain for any type of accelerators. Our evaluation on different FPGA boards shows that FOS can provide performance improvements in both single-tenant and multi-tenant environments while substantially reducing the development time and, at the same time, improving flexibility

Hypervisor Mechanisms to Manage FPGA Reconfigurable Accelerators

International audienceIn the last decade, the research on CPU-FPGA hybrid architectures has become a hot topic. One of the main challenges in this domain consists in efficiently and safely managing dynamic partial reconfiguration (DPR) resources. This paper focuses on the management of the reconfiguration by an hypervisor on an ARM-FPGA platform. Using the virtualization approach, virtual machines (VM) may access resources indepen­ dently, being unaware of the existence of other VMs. The purpose of our work is to provide an abstract and transparent interface for virtual machines to access reconfigurable resources. The underlying infrastructure of partial reconfiguration management is hidden from the virtual machines, so that software developers do not need to consider the implementation details. We propose a framework where DPR accelerators are presented as virtual devices, which are universally mapped in each VM space as ordinary peripherals. The hypervisor automatically detects VM's requests for DPR resources and handles them dynamically according to a preemptive allocation mechanism. Our custom hypervisor guarantees the independent and isolation of VM domains. We also evaluate the efficiency of our framework by measuring the critical overheads during DPR management and allocations. The results demonstrate that our mechanism is implemented with low overhead