A new technical paper, “Rethinking Compute Substrates for 3D-Stacked Near-Memory LLM Decoding: Microarchitecture-Scheduling ...
Local LLMs have this annoying middle ground problem. They're good enough that you can see the potential, but just slow enough to get in the way. You really feel the ...
“LLM decoding is bottlenecked for large batches and long contexts by loading the key-value (KV) cache from high-bandwidth memory, which inflates per-token latency, while the sequential nature of ...
This figure shows an overview of SPECTRA and compares its functionality with other training-free state-of-the-art approaches across a range of applications. SPECTRA comprises two main modules, namely ...
Edge-Centric Generative AI: A Survey on Efficient Inference for Large Language Models in Resource-Constrained Environments ...
In the rapidly evolving world of technology and digital communication, a new method known as speculative decoding is enhancing the way we interact with machines. This technique is making a notable ...
Mesh LLM is a mechanism that brings together the surplus GPU computing resources of multiple computers to enable distributed execution of large-scale language models that would be difficult to run on ...
Shakti P. Singh, Principal Engineer at Intuit and former OCI model inference lead, specializing in scalable AI systems and LLM inference. Generative models are rapidly making inroads into enterprise ...
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