In modern data management systems, directly performing operations on compressed data
has been proven to be a big success facing big data problems. These systems have …

Today's scientific high-performance computing applications and advanced instruments are
producing vast volumes of data across a wide range of domains, which impose a serious …

Stream processing prevails and SQL query on streams has become one of the most popular
application scenarios. For example, in 2021, the global number of active IoT endpoints …

Today's large-scale scientific applications running on high-performance computing (HPC)
systems generate vast data volumes. Thus, data compression is becoming a critical …

Today's graphics processing unit (GPU) applications produce vast volumes of data, which
are challenging to store and transfer efficiently. Thus, data compression is becoming a …

Stream processing has been in widespread use, and one of the most common application
scenarios is SQL query on streams. By 2021, the global deployment of IoT endpoints …

Lossless data compression has evolved into an indispensable tool for reducing data transfer
times in heterogeneous systems. However, performing decompression on host systems can …

Data compression is essential to reduce high storage and communication costs for a wide
range of systems and applications. Canonical Huffman coding plays a pivotal role for …

Today's scientific exploration is driven by large-scale simulations and advanced instruments,
generating vast amounts of data. As we advance into the era of exascale computing, the …