Introduction Building on the improvements Hammerspace introduced into the Linux kernel in 2024 to further improve Tier 0 performance, the new Hammerspace v5.2 release contains a related enhancement called Tier…
Hammerspace submitted results for the IO500 benchmark for the first time at the 2025 International Supercomputing show (ISC25). This technical brief summarizes the results of that testing.
Summary The MLCommons MLPerf Storage benchmark is designed to demonstrate the performance of data storage platforms supporting AI/ML workloads. The aim is to provide AI system architects and decision makers…
Servers equipped with GPUs are expensive but vital for modern computing, particularly projects involving AI.
Over the last few decades, file storage and object storage have evolved alongside each other, and they were largely deployed for different use cases.
This year, Hammerspace submitted results for the MLPerf v1.0 Storage Benchmark for the first time. This technical brief summarizes the results of that benchmark test
Learn how Hammerspace Erasure Coding performs up to 2x faster than traditional erasure coding schemes, while providing data storage efficiency, data durability and flexible scalability.
This technical brief offers a high-level explanation of how RDMA works, where and how it is beneficial, and the key requirements for implementing RDMA in a Hammerspace Global Data Environment.
Hammerspace software is now certified with GDS, enabling development teams to leverage the global view and parallel performance of the Hamerspace Global Data Environment to make any storage GPUDirect storage.
