Memory compressor IP can save time, energy

January 26, 2017 //By Peter Clarke
Memory compressor IP can save time, energy
ZeroPoint Technologies AB (Goteborg, Sweden) is developing a hardware-based approach to data compression called MaxiMem that could be useful for both servers and leaf node equipment.

The company is a 2015 spin-off from research conducted at Chalmers University and from participation in the EuroServer collaborative research project partially funded by the European Union (see European server project promotes ARM on FDSOI ). ZeroPoint claims it can produce memory savings of a factor of three or greater on real-life data. This in turn means less data is transferred from processor to memory and back, which saves time, and also saves energy in the communications and in the storage of that data.

Typically compression systems are designed to work with inactive data, such as compressing files for storage or for transmission, compressing inactive information/programs and with the option of more aggressive lossy compression versus milder loss-less compression.

Instead ZeroPpont has chosen to attack the larger problem of active data and multiple data types, which might include music, video, photography, text files and the multiple formats that they use and where the data may be changing. This makes it applicable both in server computers but also, potentially on smartphones and Internet of Things nodes.

The company does this via a lossless approach and an analysis of multiple data types. The fact that it addresses active data means that minimizing the latency is vital and requires a hardware based approach. As a result the company is taking a hardware IP licensing approach, similar to ARM.

"Our business model is to license IP blocks for inclusion in FPGAs as well as in SoC/processor chips," Stefan Lindeberg, CEO of ZeroPoint, told eeNews Europe in email correspondence.

Lindeberg said: "Software solutions would be way to slow. Because of our very fast algorithms/implementations we manage to compress very effectively at memory speed." He added: "For active data, the compression has to work at the 'speed of memory' with nanosecond or even without latency in order not to reduce performance. Adding compression without adding latency might seem contradictory but since MaxiMem reduces the actual data

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