  We present RDMAbox, a set of low level RDMA opti-mizations that provide
better performance than previous ap-proaches. The optimizations are packaged in
easy-to-use ker-nel and userspace libraries and presented through simple
nodelevel abstractions. We demonstrate the flexibility and effec-tiveness of
RDMAbox by implementing a kernel remote pag-ing system and a userspace file
system using RDMAbox.RDMAbox employs two optimization techniques. First,
wesuggest Load-aware Batching to further reduce the total num-ber of I/O
operations to the RDMA NIC beyond existing door-bell batching. The I/O merge
queue at the same time functionsas a traffic regulator to enforce admission
control and avoidoverloading the NIC. Second, we propose Adaptive Pollingto
achieve higher efficiency of polling Work Completion thanexisting busy polling
while maintaining the low CPU over-head of event trigger. Our implementation of
a remote paging system with RDMAbox outperforms existing representative
solutions with up to 6.48x throughput improvement and up to 83% decrease in
average tail latency in bigdata workloads, and up to 83% reduction in
completion time in machine learn-ing workloads. Our implementation of a user
space file system based on RDMAbox achieves up to 6x higher throughput over
existing representative solutions.
