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 ...

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 ...

One of the greatest challenges facing the designers of many-core processors is resource contention. The chart below visually lays out the problem of resource contention, but for most of us the idea is ...

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 ...

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 ...

System-on-chip (SoC) architects have a new memory technology, last level cache (LLC), to help overcome the design obstacles of bandwidth, latency and power consumption in megachips for advanced driver ...

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 ...