Use Case: Data Centers

Data Centers Deep Learning Challenges

After a deep learning model is trained, the resulting model typically consumes lots of memory and requires dedicated hardware (e.g. GPUs) for deployment (inference mode). Consequently, deep learning deployment today is limited mostly to cloud, and even there, involves huge costs for expensive processors, large amounts of memory, and especially high electricity costs, due to intensive computing requirements.

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Data Centers Deep Learning Challenges

After a deep learning model is trained, the resulting model typically consumes lots of memory and requires dedicated hardware (e.g. GPUs) for deployment (inference mode). Consequently, deep learning deployment today is limited mostly to cloud, and even there, involves huge costs for expensive processors, large amounts of memory, and especially high electricity costs, due to intensive computing requirements.

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DeepCube Applies to Large Scale AI Deployments Cross Industries

DeepCube’s inference accelerator, resulting in a drastic improvement of deep learning speed on any existing hardware, is optimized for large enterprises (huge databases, heavy computing processes, data crunching, workloads, etc.). This covers the entire AI deployment market, in any sector or industry, including:

  • Retail
  • Financial Institutions
  • Healthcare
  • Government
  • And more
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DeepCube Applies to Large Scale AI Deployments Cross Industries

DeepCube’s inference accelerator, resulting in a drastic improvement of deep learning speed on any existing hardware, is optimized for large enterprises (huge databases, heavy computing processes, data crunching, workloads, etc.). This covers the entire AI deployment market, in any sector or industry, including:

  • Retail
  • Financial Institutions
  • Healthcare
  • Government
  • And more

Significant Workload Improvement on Top of Any Hardware

DeepCube’s proprietary framework can be deployed on top of any existing hardware and results in over 10x speed improvement and memory reduction:

  • Major speed improvement for any existing hardware (even the newest)
  • No hardware upgrade needed – costs reduction by performing a simple software upgrade in order to obtain the same (or oven better) performance level
  • Major reduction in memory requirements
  • Substantial reduction in power consumption
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Significant Workload Improvement on Top of Any Hardware

DeepCube’s proprietary framework can be deployed on top of any existing hardware and results in over 10x speed improvement and memory reduction:

  • Major speed improvement for any existing hardware (even the newest)
  • No hardware upgrade needed – costs reduction by performing a simple software upgrade in order to obtain the same (or oven better) performance level
  • Major reduction in memory requirements
  • Substantial reduction in power consumption

Data Centers Companies, Transform Your Business

With DeepCube, benefit from massive gains in performance