Currently, TMO enables transparent memory offloading across millions of servers in our datacenters, resulting in memory savings of 20%–32%. Of this, 7%–19% is from the application containers, while ...

A research team from Sakana AI, Japan, has introduced Neural Attention Memory Models (NAMMs). NAMMs are a new class of memory management models that dynamically optimize the KV cache in transformers.

The performance should be fine-tuned for the Java applications so that the developed software does not become slow. How your application is going to be perceived by the user depends on the kind of ...

Learn how to optimize JVM and JIT compiler performance for better execution speed, memory usage, and resource utilization in your Java applications—and how to check your results.

Enterprise Performance Pack is a drop-in replacement for Java 8 that promises significant improvements in memory management and performance.

In this Java performance tuning guide, learn how to put together an application performance manifesto and how to investigate shared resources that might cause a Java performance problem.

Performance profiling should be an important part of your DevOps strategy. Follow these five Java performance profiling tips to optimally tune your JVM or troubleshoot runtime issues.

Java Memory Trajectory Forecasting is the primary work for energy consumption optimization of memory management system on Java platform. Based on the characteristic of Java memory management, this ...