Renowned futurist John Naisbitt once said, “We are drowning in information but starved for knowledge.”
This profound statement is even more relevant today in an era where vast amounts of data are being generated at rates beyond our ability to extract meaningful information from it and act on it in a timely manner. Advances in data analytics can help us identify threats, catch disease outbreaks, and uncover hidden relationships among data elements and categories.
For many decades, the industry utilized general purpose processors as the most efficient way of addressing deep learning computational needs. With the slowing down of Moore’s Law, we are at an inflection point. We are now entering an era where special purpose processors can provide orders of magnitude improvement in energy efficiency. New accelerator solutions provide an opportunity for deep learning to be functional and accessible, by dramatically reducing the cost and power consumption relative to GPUs and general purpose CPUs.
Qualcomm Intelligent Solutions, Inc. (QISI) is one of just two silicon technology providers selected by the U.S. Government’s Defense Advanced Research Projects Agency (DARPA) to perform breakthrough architectural work on a graph analytics processor as a part of the HIVE (Hierarchical Identify Verify Exploit) project. Per DARPA, if HIVE is successful, it could deliver a graph analytics processor that achieves a thousandfold improvement in processing efficiency over today’s best processors, enabling the real-time identification of strategically important relationships as they unfold in the field rather than relying on after-the-fact analyses in data centers.
The HIVE project will be performed in three phases over the next four and a half years, with three technical areas:
- Graph analytics processor
- Graph analytics toolkits
- System evaluation
QISI will be collaborating with the DARPA team, and other HIVE project performers that include a national laboratory, a university, and a veteran defense-industry company. The challenge we have accepted will require all of us to work together on the hardware, software tools and algorithms.
QISI has kicked off an initiative called Project Honeycomb to support this important effort. QISI’s goal with Project Honeycomb is to develop a domain-specific processor design and scalable multi-node architecture for the HIVE project. The work is intended to produce a hardware accelerator for graph computation primitives, a memory controller that optimizes data movement based on sparse mapping, and network architecture to avoid congestion in data movement. QISI plans to deliver the Project Honeycomb architecture specification and simulator to DARPA and other HIVE project performers in 12 months. The next two phases entail the design and fabrication of the graph analytics processor and delivery of a functioning 16-node system to DARPA for evaluation.
We are excited about the innovation potential of this research project that we believe will help define future architectures for graph analytics. In addition, we expect Project Honeycomb and the HIVE project as a whole will help accelerate the development of commercial products using a new innovative architectural approach for many areas related to data analytics and artificial intelligence.