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

Productive Development of Scalable Network Functions with NFork