WekaIO,
the innovation leader in high-performance, scalable file storage for
data intensive applications, today announced that it has become a
supporting organization of the MLPerf benchmark suite. Alongside
companies like NVIDIA, NetApp and Qualcomm, WekaIO will contribute its
expertise to efforts to define the machine learning (ML) benchmarks for
the industry.
MLPerf's
objective is to build a common set of benchmarks that enables the ML
field to measure system performance for both training and inference from
mobile devices to cloud services. The organization is a consortium of
researchers from prestigious universities in the United States along
with leaders in ML such as Baidu, Intel, Google and others. The recently
released MLPerf v0.5 benchmark is the industry's first objective
performance test for training algorithms to perform tasks such as
computer vision, language translation, personalized recommendations, and
reinforcement learning.
"We
have demonstrated that WekaIO Matrix delivers superior performance
benefits and is uniquely positioned to be the best storage solution for
ML workloads," said Barbara Murphy, Vice President of Marketing at
WekaIO. "Our customers are using Matrix to accelerate ML workloads at
scale. Matrix is the only file system today that can keep GPUs and CPUs
saturated with data, eliminating the IO constraints commonly associated
with legacy storage systems. For successful ML outcomes, it's critical
for organizations to consider the underlying storage infrastructure. So,
we are honored to contribute our knowledge and proficiency to the
MLPerf benchmark which, when established, will help organizations make
better informed infrastructure decisions."
In addition, WekaIO participates in the well-established SPEC SFS benchmark-a
standard for high-performance computing (HPC) performance-and a
proponent of the importance of delivering performance standards for the
ML and HPC industry at large.