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·
Running ML on Von Neumann CPU |
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· Statistical Consistency Selective Availability |
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· Constant time for Learning and Inference |
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· Continuous Learning ( Plasticity + Stability ) |
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· Huge Datasets Management |
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· Hardware Adaptive Technology |
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· t = log2 ( parameters ) |
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Mythos™ is a technology
designed to obtain SIMD (Single Instruction Multiple Data) parallelism on a
Von Neumann machine, for Pattern Recognition problems. Although the current
processors are "Multi-Core", they cannot be compared to SIMD / MIMD
(Multiple Instructions Multiple Data) processors, especially due to the limited
number of cores, and are still considered as Von Neumann machines. For this
reason there are GPU coprocessors that serve to have massive parallelism of
the SIMD and MIMD type. In many cases it is not possible or not desirable to
use parallel coprocessors: the algorithms of Mythos™ technology are designed for Pattern Recognition
applications with the aim of increasing the performance on Von Neumann
machines by orders of magnitude when a SIMD parallelism would be required by
the application. In particular, the Mythos™ technology is oriented towards Pattern
Recognition applications in the Aerospace sector, where Radiation-Hardened
processors / SBCs such as the RAD750® produced by BAE Systems must
be used. RAD750® SBC is the workhorse of the space industry, powering more
than 100 satellites that carry out a variety of space missions.
Radiation-Hardened processors must operate at lower cock frequencies than
those typically used by processors operating in sectors that do not have this
criticality. The need for execution speed in algorithms seems
now forgotten due to the widespread use of parallel SIMD and / or MIMD
processors such as high clock frequency GPUs. In
reality, there are sectors, such as aerospace, in which high clock
frequencies cannot be used and given that Radiation-Hardened GPUs have not yet been implemented, the research on
algorithms that allow to speed up Pattern
Recognition problems by orders of magnitude becomes a current need. |
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LUCA MARCHESE Aerospace_&_Defence_Machine_Learning_Company VAT:_IT0267070992 Email:_luca.marchese@synaptics.org |
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