Overview
MemComputing, Inc.’s disruptive MemCPU™ Coprocessor technology is accelerating the time to find feasible solutions to the most complex optimization problems in all industries. Using a physics-based approach, this novel architecture is based on the computational efficiencies of the human brain. MemComputing liberates users from modern computational bottlenecks, enabling companies to accurately analyze huge amounts of data in minutes or seconds, empowering them to make optimal business decisions today.
Optimization Problems Are Everywhere
These fundamental problems pervade essentially every scientific discipline and industry and are usually difficult to solve
Life Sciences
Drug Design
Finance
Portifolio Optimization
Energy
Demand Forecasting
Machine Learning
Deep Learning
Logistic & Distribution
Resource Planning
Optimization problems involve finding the best solution from all possible solutions; often exploring millions, billions or even more possible combinations
One approach is to exhaustively search and check every possible solution but this “brute force” becomes less and less feasible as problems get bigger
For many optimization problems, the time required to solve grows exponentially as more variables are added often rendering them intractable for modern computers
An Exponential Problem
Exponential problems are often called “intractable” since they can take longer than a lifetime to solve
Currently, many known solutions for optimization problems involve exponential growth
-
Complex optimization problems are often classified as “NP-hard“ or “NP-Complete”.
“NP” problems are problems which are unsolvable within a reasonable amount of time for large input sizes.
-
The “Time Complexity” of a problem defines how the time to solve increases with input size
-
O(n) – Execution time increases linearly with input size
-
O(n^2 ) – Quadratic Growth
-
O(2^n ) – Exponential Growth
Exponential problems are often called “intractable” since they can take longer than a lifetime to solve
What to do?
If most optimization problems are intractable, how do we solve them?
For many years, research has been focused on developing computer systems and techniques that could efficiently solve these NP problems. However many challenges remain.
Select Techniques and Systems for Approaching Intractable Optimization Problems
Branch & Bound
Heuristics
A technology that can efficiently provide accurate solutions to these exponential problems stands to unlock tremendous value across a number of industrial & scientific verticals
MemComputing’s New Approach
A proprietary computing architecture that achieves an exponential speed-up and finds better solutions
-
Inspired by the computational efficiency of the brain
-
Fundamentally different computational architecture
-
Introduces “Self Organizing Logic Gates” – accepting inputs form any terminal which enable collective behavior
-
Takes advantage of non-locality of memory and long range correlations between gates
-
Completely avoids the von Neumann Bottleneck
Types of Applications/Customers
MEMCPU™ can scale to address challenging problems for a wide variety of industries and application
