Memory-Converged Infrastructure (MCI)
Customer Use Cases

AI Training with Checkpointing

Problems
  • Model training takes a long time to complete for large datasets
  • Failure recovery is painful without frequent checkpointing
  • Data preprocessing and importing can take a long time
  • Delayed model deployment
Solution
  • MemVerge DMO, powered by Optane DC persistent memory, improves checkpointing speed and data loading speed
MemVerge Customer Use-Case: AI Training

up to

6X

Training Speed

up to

350X

Data Import Speed

Instant

Checkpoint Recovery

AI Training with GraphSAGE

Problems
  • Graphical Convolutional Network model with excellent performance for large Social Network recommendation
  • 24 TB memory required to effectively run a large workload with over 500 million nodes
  • Also, slow loading of training data from storage
Solution
  • Intel Optane DC Persistent Memory expands to terabytes of memory
  • MemVerge DMO extends memory and provides fast data loading
MemVerge Use Case: AI with GraphSage

Projected

10x

Cost Saving

Projected

3x

AI Training Speed

Greener

For the Environment

Big Data Analytics with Spark

Problem
  • Spark SQL Out of DRAM
  • Disk I/O too slow
  • Data spill degrades performance
  • Local SSDs wear out by frequent intermediate data writes
Solution
  • Adding MemVerge DMO to the Spark cluster accelerates the entire cluster
  • Moving intermediate state off Spark Elastic Computing nodes increased the cloud elasticity of the solution
Customer Use Case: Data Warehouse

5X

Terasort Speed

7X

RDD Caching Speed

100%

Cloud Elasticity