Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...

SAN FRANCISCO--(BUSINESS WIRE)--Today, MLCommons ® announced new results for the MLPerf ® Training v4.0 benchmark suite, including first-time results for two benchmarks: LoRA fine-tuning of LLama 2 ...

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...

“Training on large graph-structured datasets poses unique system challenges, demanding optimizations for sparse operations and inter-node communication. We hope the addition of a GNN based benchmark ...

A research team has recently demonstrated that analog hardware using ECRAM devices can maximize the computational performance of artificial intelligence, showcasing its potential for commercialization ...

Scientists develop next-generation semiconductor technology for high-efficiency, low-power artificial intelligence. A research team, consisting of Professor Seyoung Kim from the Department of ...

With a solution that combines leading-edge hardware with specialized software, GIGABYTE is making it possible to train your own AI on your desk, unlocking benefits like flexibility, upgradeability, ...

Chinese researchers harness probabilistic updates on memristor hardware to slash AI training energy use by orders of magnitude, paving the way for ultra-efficient electronics.