Publication
Shared Virtual Memory (SVM) is a mechanism that allows host-side applications and FPGA accelerators to access the same virtual address space. It enables accelerating algorithms with unpredictable memory access patterns by making transparent pointer sharing possible. Even for applications with predictable memory access patterns, SVM helps by eliminating manual data movement. FlexiMem is a customizable SVM system that uses FPGA-addressable memory resources to store virtual memory pages, rather than directly accessing the host memory, to achieve high throughput and low latency. On the FPGA side, FlexiMem features a highly-flexible interconnect that, for the first time, allows for configuring address and payload data paths independently for SVM systems. It supports multiple master and slave devices sharing the same address space, such as accelerators issuing many memory requests in parallel to multiple memory banks. With our interconnect design, we provide numerous specialization dimensions to optimize the SVM system for a given workload. For example, irregular applications with short accesses to memory require an address translation for each data transfer. Such applications can take advantage of a highly parallelized address data path and an increased number of TLBs working in parallel. In contrast, regular and bursting applications transfer a small number of address packets per many data packets, and they can tolerate a lightweight address data path with a single translation unit. FlexiMem also provides address translation units with reconfigurable capacities and page sizes to be tailored to the needs of the application. On the host side, FlexiMem leverages the Linux userfaultfd API and vendor-provided IPs and drivers for automatic data movement initiated by software. Blocks of memory allocated by the FlexiMem API can be passed freely to the FPGA or other host-side libraries, without requiring any kind of explicit data movement. We evaluate several experimental setups with various FlexiMem configurations to showcase the effect of customizability on performance.