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 ...

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 ...

Linux is a powerful and flexible operating system, widely used in servers, embedded systems, and even personal computers. However, even the best-configured systems can face performance bottlenecks ...

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.

Domain-specific computing may be all the rage, but it is avoiding the real problem. The bigger concern is the memories that throttle processor performance, consume more power, and take up the most ...

Fine-tuning large language models in artificial intelligence is a computationally intensive process that typically requires significant resources, especially in terms of GPU power. However, by ...