In-Memory / Cognitive Intelligence Computing Research Service (RS601-2016)

This service comprises studies that analyze Real-Time analytic solutions using In-Memory Compute architectures.

Mounting entire database images into large main memory (DRAM) arrays achieves the desired throughput data rate necessary to achieve real-time performance on Big Data. This architecture is also completely capable of running Cognitive Intelligent Computing applications.

What are the present and future impacts on Flash memory, Storage Class Memory (memory / storage) and DRAM.

These research services can be tailored for in-depth strategic planning. Through careful analysis of our client's company goals, financial condition, and competitive position, we assist them in developing, implementing, and monitoring strategies that assist with transitioning to memory centric computing as well as aligning economic, market directions and forecasts.

Real-Time Analytics - Impact on Semiconductor Markets (RS600RTA-2016) 

This portfolio comprises a subject series that analyze emerging market solutions for In-Memory Computing inclusive of first generation persistent memory platforms. Subjects covered include the application of intelligence to direct attached Flash Storage, Memory Channel NVDIMM and DRAM/XPoint technologies.

Additional subject matter includes the application of these technologies within the Data-Appliance market segment and the extension of Data-Appliance architectures into the cognitive computing data space.

Included in this report is an extended forecast detailing the market crossover from Flash based to XPoint/Resistive based memory and Hybrid Memory Cube / High Bandwidth Memory FPGA technologies.

Artificial Intelligence - Present and Future Influence on Semiconductor Markets (RS625AI-2016) 

This portfolio comprises a subject series that analyze current and projected semiconductor usage within the emerging Cognitive Computing market segment. Emphasis is placed on technologies which reduce power, increase performance capability at lower cost.

Subjects include DRAM/Flash/XPoint hybrid model and implementation; emergence of, and application of neuromorphic computing, and their impact on the von Neumann architecture.

This is an annual subscription service