The dynamic interplay between processor speed and memory access times has rendered cache performance a critical determinant of computing efficiency. As modern systems increasingly rely on hierarchical ...

Google has published TurboQuant, a KV cache compression algorithm that cuts LLM memory usage by 6x with zero accuracy loss, ...

Google researchers have published a new quantization technique called TurboQuant that compresses the key-value (KV) cache in ...

Researchers at the Tokyo-based startup Sakana AI have developed a new technique that enables language models to use memory more efficiently, helping enterprises cut the costs of building applications ...

Cache memory significantly reduces time and power consumption for memory access in systems-on-chip. Technologies like AMBA protocols facilitate cache coherence and efficient data management across CPU ...

The biggest memory burden for LLMs is the key-value cache, which stores conversational context as users interact with AI ...

Embedded systems demand high performance with minimal power consumption, and the optimisation of scratchpad memory (SPM) plays a critical role in meeting these stringent requirements. SPM, a small ...

In the eighties, computer processors became faster and faster, while memory access times stagnated and hindered additional performance increases. Something had to be done to speed up memory access and ...

Google’s announcement of TurboQuant is weighing on the share prices of memory companies, as the technology is expected to cut ...