  Despite decades of research, developing correct and scalable concurrent
programs is still challenging. Network functions (NFs) are not an exception.
This paper presents NFork, a system that helps NF domain experts to
productively develop concurrent NFs by abstracting away concurrency from
developers. The key scheme behind NFork's design is to exploit NF
characteristics to overcome the limitations of prior work on concurrency
programming. Developers write NFs as sequential programs, and during runtime,
NFork performs transparent parallelization by processing packets in different
cores. Exploiting NF characteristics, NFork leverages transactional memory and
develops efficient concurrent data structures to achieve scalability and
guarantee the absence of concurrency bugs.
  Since NFork manages concurrency, it further provides (i) a profiler that
reveals the root causes of scalability bottlenecks inherent to the NF's
semantics and (ii) actionable recipes for developers to mitigate these root
causes by relaxing the NF's semantics. We show that NFs developed with NFork
achieve competitive scalability with those in Cisco VPP [16], and NFork's
profiler and recipes can effectively aid developers in optimizing NF
scalability.
