University of Wisconsin-La Crosse
With the advent of general-purpose GPU computing, it is becoming increasingly desirable to protect GPUs from soft errors. For high computation throughout, GPUs must store a significant amount of state and have many execution units. The high power and area costs of full protection from soft errors make selective protection techniques attractive. Such approaches provide maximum error coverage within a fixed area or power limit, but typically treat all errors equally. The authors observe that for many floating-point-intensive GPGPU applications, small magnitude errors may have little effect on results, while large magnitude errors can be amplified to have a significant negative impact.