  In this paper, we show that using Intelligent Reflecting Surfaces (IRS) can
enhance the computing capability of a wireless network scenario. We consider a
Multiple Access Channel (MAC) where a number of users aim to send data to a
Base Station (BS). The BS is interested in decoding a linear combination of the
data from different users in the corresponding finite field. By focusing on the
Compute-and-Forward framework, we show that through carefully choosing the IRS
parameters, such a scenario's computation rate will be significantly improved.
More specifically, we formulate an optimization problem to maximize the
computation rate and tackle the problem via an alternating optimization (AO)
approach. Our results confirm the usefulness of IRS technology for future
wireless networks -- such as 6G -- with massive computation requirements.
