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DisGCo: A Compiler for Distributed Graph Analytics
, Rajendran A.
Published in ACM
Volume: 17
Issue: 4
Graph algorithms are widely used in various applications. Their programmability and performance have garnered a lot of interest among the researchers. Being able to run these graph analytics programs on distributed systems is an important requirement. Green-Marl is a popular Domain Specific Language (DSL) for coding graph algorithms and is known for its simplicity. However, the existing Green-Marl compiler for distributed systems (Green-Marl to Pregel) can only compile limited types of Green-Marl programs (in Pregel canonical form). This severely restricts the types of parallel Green-Marl programs that can be executed on distributed systems. We present DisGCo, the first compiler to translate any general Green-Marl program to equivalent MPI program that can run on distributed systems. Translating Green-Marl programs to MPI (SPMD/MPMD style of computation, distributed memory) presents many other exciting challenges, besides the issues related to differences in syntax, as Green-Marl gives the programmer a unified view of the whole memory and allows the parallel and serial code to be inter-mixed. We first present the set of challenges involved in translating Green-Marl programs to MPI and then present a systematic approach to do the translation. We also present a few optimization techniques to improve the performance of our generated programs. DisGCo is the first graph DSL compiler that can handle all syntactic capabilities of a practical graph DSL like Green-Marl and generate code that can run on distributed systems. Our preliminary evaluation of DisGCo shows that our generated programs are scalable. Further, compared to the state-of-the-art DH-Falcon compiler that translates a subset of Falcon programs to MPI, our generated codes exhibit a geomean speedup of 17.32×. © 2020 ACM.
About the journal
JournalACM Transactions on Architecture and Code Optimization
Open AccessNo