Researchers from Durham University and a number of international collaborators (University of Essex (UK), IISER Bhopal (India), NTNU (Norway)) have developed a new hybrid technique, PRECIOUS, which enhances the performance and energy efficiency of approximate real-time computing systems. This innovation addresses the conflicting demands of time-critical applications by optimising how tasks are scheduled and managed on heterogeneous computing platforms.

Optimising Approximate Computing

In approximate computing, an on-time, slightly less precise result is preferred over a late but perfectly accurate one. This approach is common in applications like mobile target tracking and multimedia processing. The new research, outlined in a paper titled "PRECIOUS: Approximate Real-Time Computing in MLC-MRAM based Heterogeneous CMPs" , tackles the challenge of maximising the Quality of Service (QoS) of these tasks while staying within power limits and meeting deadlines.

A Two-Staged Approach

PRECIOUS employs a hybrid offline-online method to achieve its goals.

• Offline Scheduling: The PRECIOUS-Offline component first creates an optimal schedule for real-time tasks on a heterogeneous multicore platform. This phase maximises QoS by assigning tasks to either high-performance (HP) or low-performance (LP) cores, while respecting power, deadline, and task-dependency constraints. For a specific task set, this offline approach alone achieved up to 76% QoS, outperforming previous methods.
• Online Optimisation: The PRECIOUS-Online component refines the schedule at runtime. It uses a novel architectural technique that leverages the higher storage density of multilevel-cell (MLC) MRAM-based cache memories. By intelligently managing data blocks in the last level cache, the technique reduces cache miss rates by 19%, leading to a significant improvement in performance without increasing energy consumption compared to conventional MRAM designs. The improved performance creates "slacks" or unused time, which is then opportunistically used to either execute higher-quality versions of tasks to boost QoS or to turn off processor cores to save energy. This runtime approach enhances QoS by 9.0% on average.

The Technology Behind the Breakthrough

A key element of PRECIOUS is its use of MLC-MRAM, a type of non-volatile memory that offers double the storage density of traditional MRAM. This allows for a larger, more efficient last-level cache (LLC). The researchers developed a new block management technique, called as MLC_In_S_Out_HS, to mitigate the high write latency and energy consumption associated with hard bits in MLC-MRAM. This technique prioritises placing data from energy-efficient in-order (InO) cores in the faster "soft-bit" region of the cache, while also directing some requests from high-performance out-of-order (OoO) cores to this region. This helps maintain performance while saving energy.

Impact and Future Work

This research represents the first work to maximise QoS for a dependent approximate time-critical task set on a heterogeneous multicore processor by using a novel scheduling strategy and a MLC-MRAM-based cache. The hybrid approach provides a robust solution for a wide range of real-time applications where power consumption and time criticality are contradictory constraints.

Further research is planned to extend PRECIOUS to support concurrent task execution within clusters and to incorporate dynamic voltage and frequency scaling (DVFS) and task migration strategies to further improve performance and energy efficiency.

Find Out More

• This research was co-authored by Dr. Shounak Chakraborty from our Department of Computer Science.
• Read the full paper published in IEEE Transactions on Computers.
• Durham University is The Times and The Sunday Times University of the Year 2026 and ranked third overall in its Good University Guide. Interested in studying at Durham? Explore our undergraduate and postgraduate courses.