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

Adarsh Mittal, a senior application-specific integrated circuit engineer, explores why many memory performance optimizations ...

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working ...

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 ...

Modern multicore systems demand sophisticated strategies to manage shared cache resources. As multiple cores execute diverse workloads concurrently, cache interference can lead to significant ...

As AI workloads extend across nearly every technology sector, systems must move more data, use memory more efficiently, and respond more predictably than traditional design methodologies allow. These ...