LLMs bring a new level of natural language processing and understanding capabilities, making them versatile tools for enhancing communication, automation, and data analysis tasks. They unlock new capabilities in chatbots, content generation, language translation, sentiment analysis, text summarization, question-answering systems, and personalized recommendations. Due to their large model size and the extensive processing required, most LLM-based applications have been confined to the cloud. However, many OEMs want to reduce reliance on costly, overburdened data centers by deploying LLMs at the edge. Additionally, running LMM-based applications on edge devices improves reliability, reduces latency, and provides a better user experience.
"Edge AI designs require a careful balance of performance, power consumption, area, and latency," said Da Chuang, co-founder and CEO of Expedera. "Our architecture enables us to customize an NPU solution for a customer's use cases, including native support for their specific neural network models such as LLMs. Because of this, Origin IP solutions are extremely power-efficient and almost always outperform competitive or in-house solutions."
Expedera's patented packet-based NPU architecture eliminates the memory sharing, security, and area penalty issues that conventional layer-based and tiled AI accelerator engines face. The architecture is scalable to meet performance needs from the smallest edge nodes to smartphones to automobiles. Origin NPUs deliver up to 128 TOPS per core with sustained utilization averaging 80%—compared to the 20-40% industry norm—avoiding dark silicon waste.
For more information or to contact an Expedera representative in your region, visit www.expedera.com.
About Expedera
Expedera provides customizable neural engine semiconductor IP that dramatically improves performance, power, and latency while reducing cost and complexity in edge AI inference applications. Successfully deployed in over 10 million consumer devices, Expedera's Neural Processing Unit (NPU) solutions are scalable and produce superior results in applications ranging from edge nodes and smartphones to automotive. The platform includes an easy-to-use TVM-based software stack that allows the importing of trained networks, provides various quantization options, automatic completion, compilation, estimator, and profiling tools, and supports multi-job APIs. Headquartered in Santa Clara, California, the company has engineering development centers and customer support offices in the United Kingdom, China, Japan, Taiwan, and Singapore. Visit
https://www.expedera.com
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SOURCE Expedera, Inc
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