However, software compression adds substantial overheads, and prior hardware compression techniques work poorly on the complex access patterns of irregular applications.We present SpZip, an ...

Optimizing data compression methods has become more critical than ever for cloud storage, data management, and streaming applications. Working with compressed data reduces network bandwidth, data ...

The President of ZeoSync Corp. compresses data by reducing the expression of random information sequences. Existing compression technologies depend on mapping and encoding of redundant mathematical ...

Lossy data compression is used in applications where an acceptable amount of data loss is allowed in the compression algorithm. We see lossy data compression predominantly in the areas of imagery, ...

A novel technique rethinks hardware data compression to free up more memory used by computers and mobile devices, allowing them to run faster and perform more tasks simultaneously.

For applications that do not require compression and decompression to be accomplished particularly fast, a CPU is sufficient. When it comes to higher performance applications such as those involved ...

In a video transcoding application, Samsung measured an 80% boost in performance by breaking up processing between the CPU and FPGA on the SmartSSD, and that reduced server CPU utilization from 93% to ...

Trajectory data compression and simplification techniques have emerged as essential tools for managing the ever‐increasing volumes of spatio‐temporal data generated by GPS devices and other ...

Typical applications for lossy compression include audio and video compression. Lossless compression is used for applications where the original data must be fully restored following decompression.

Imagine a 100GB movie in a text! Anthony Ravenberg's quantum compression shatters limits, offering extreme data reduction and quantum-resistant security.

Genomic data compression techniques have emerged as indispensable tools in addressing the exponential growth of sequencing data, which poses significant challenges in storage, processing, and ...