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New multi-threading technique promises to double processing speeds | 'SHMT' also sliced power usage by 51% compared to existing techniques
Researchers at the University of California Riverside developed a technique called Simultaneous and Heterogeneous Multithreading (SHMT), which builds on contemporary simultaneous multithreading. Simultaneous multithreading splits a CPU...
This part of the process aims to balance performance and precision by assigning tasks requiring high accuracy to the CPU rather than the more error-prone AI accelerator, among other things. Early proof-of-concept trials utilized Nvidia's Jetson Nano board containing a 64-bit quad-core Arm CPU, 128-core Maxwell GPU, 4GB RAM, and an M.2 slot housing one of Google's Edge TPU AI accelerators. However, the research does sound promising, given the explosion in generative AI apps over the past couple of years and the sheer amount of processing power it takes to run them.
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