Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...
Forged in collaboration with founding contributors CoreWeave, Google Cloud, IBM Research and NVIDIA and joined by industry leaders AMD, Cisco, Hugging Face, Intel, Lambda and Mistral AI and university ...
NVIDIA Boosts LLM Inference Performance With New TensorRT-LLM Software Library Your email has been sent As companies like d-Matrix squeeze into the lucrative artificial intelligence market with ...
MLCommons, the open engineering consortium for benchmarking the performance of chipsets for artificial intelligence, today unveiled the results of a new test that’s geared to determine how quickly ...
Using the AIs will be way more valuable than AI training. AI training – feed large amounts of data into a learning algorithm to produce a model that can make predictions. AI Training is how we make ...
The history of computing teaches us that software always and necessarily lags hardware, and unfortunately that lag can stretch for many years when it comes to wringing the best performance out of iron ...
The AI chip giant says the open-source software library, TensorRT-LLM, will double the H100’s performance for running inference on leading large language models when it comes out next month. Nvidia ...
A new technical paper titled “Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference” was published by researchers at University of Cambridge, Imperial College London ...
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