Imagine doubling the speed of your old PC without spending a dime on new hardware. That’s exactly what researchers are exploring with a breakthrough system called simultaneous and heterogeneous multithreading (SHMT). This innovative approach could transform how we think about PC performance, delivering faster speeds without the need for costly upgrades.
The research, led by a team from the University of California, Riverside, highlights the wide-ranging potential of SHMT technology. Beyond simply making computers run faster, the system could improve hardware efficiency while reducing overall energy consumption. If successful, this could benefit not only everyday PC users but also industries that rely heavily on computing power.
This PC performance breakthrough works by tapping into the fact that today’s computers, smartphones, and other devices rely on multiple processors to manage tasks. From the CPU to the GPU and even to specialized parts like the TPU (tensor processing unit), each handles different workloads to keep systems running smoothly. However, this division of labor can also create data bottlenecks as information moves between processors, slowing down overall performance.
How SMHT Boosts Speed and Cuts Energy Use in PCs
This is where simultaneous and heterogeneous multithreading (SHMT) makes a difference. By allowing tasks to run simultaneously across multiple processors, SHMT improves overall efficiency while reducing energy demands. Because the workload is evenly distributed, systems don’t need as much power to handle complex operations. In testing, researchers recorded performance gains of up to 1.95x faster speeds, along with an impressive 51% reduction in energy consumption.
However, bringing this PC breakthrough to mainstream devices isn’t without its challenges. SHMT must undergo rigorous quality assurance testing to confirm that different processor architectures don’t introduce precision mismatches. That means SHMT isn’t likely to roll out widely just yet. Any early adoption will be limited until researchers can ensure that the performance and efficiency improvements work consistently across devices. Details of the research were published in a paper presented at the 56th annual IEEE/ACM International Symposium on Microarchitecture in Toronto, Canada.