  Low-power small form factor data processing units (DPUs) enable offloading
and acceleration of a broad range of networking and security services. DPUs
have accelerated the transition to programmable networking by enabling the
replacement of FPGAs/ASICs in a wide range of network oriented devices. The
GraphBLAS sparse matrix graph open standard math library is well-suited for
constructing anonymized hypersparse traffic matrices of network traffic which
can enable a wide range of network analytics. This paper measures the
performance of the GraphBLAS on an ARM based NVIDIA DPU (BlueField 2) and, to
the best of our knowledge, represents the first reported GraphBLAS results on a
DPU and/or ARM based system. Anonymized hypersparse traffic matrices were
constructed at a rate of over 18 million packets per second.
