CogniMem Technologies has unveiled the industry’s first greater than 40,000-neuron, scalable cognitive memory computing system based on CogniBlox, a memory-based parallel processing capability that architecturally implements how the human brain processes data.

With architectural re-configurability and local magnetoresistive random-access memory (MRAM), the CogniBlox system can scale to very large arrays of cognitive memory and configurations. The result is a platform for deployment of real artificial intelligence with exceptional speed performance and low power consumption.

The memory system consists of 10 CogniBlox boards, offering a large bank of cognitive memories with no impact on operation and enabling a path to exascale computing for a wide range of data-mining applications.

'Our cognitive memory system most quickly allows you to find your proverbial needle in the haystack. It’s based on CogniBlox architecture that features multiple chips working on the same task in parallel, processing complicated functions just like the brain does, said Bruce McCormick, co-founder of CogniMem.

'CogniBlox processes and accesses memory in pure parallel, presenting a marked departure from traditional computing techniques that have memory bottlenecks and synchronisation and communication difficulties.'


For functionality and security for externalised research, software providers have turned to the cloud, writes Sophia Ktori


Robert Roe looks at the latest simulation techniques used in the design of industrial and commercial vehicles


Robert Roe investigates the growth in cloud technology which is being driven by scientific, engineering and HPC workflows through application specific hardware


Robert Roe learns that the NASA advanced supercomputing division (NAS) is optimising energy efficiency and water usage to maximise the facility’s potential to deliver computing services to its user community


Robert Roe investigates the use of technologies in HPC that could help shape the design of future supercomputers