Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.
Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
Detailed in a recently published technical paper, the Chinese startup’s Engram concept offloads static knowledge (simple ...
South Korean AI chip startup FuriosaAI scored a major customer win this week after LG's AI Research division tapped its AI accelerators to power servers running its Exaone family of large language ...
TOKYO--(BUSINESS WIRE)--Kioxia Corporation, a world leader in memory solutions, has successfully developed a prototype of a large-capacity, high-bandwidth flash memory module essential for large-scale ...
A new technical paper titled “Accelerating LLM Inference via Dynamic KV Cache Placement in Heterogeneous Memory System” was published by researchers at Rensselaer Polytechnic Institute and IBM. “Large ...
What just happened? At its first big investor event since breaking off from Western Digital, SanDisk unveiled something it's been cooking up to take a bite out of the hot AI market. The company has a ...
The scaling of computational power within a single, packaged semiconductor component continues to rise following a Moore’s law type curve enabling new and more capable applications including machine ...
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