This paper proposes a stacked intelligent metasurface (SIM)-aided holographic MIMO (HMIMO) architecture for the uplink of cell-free networks. The SIM is deployed at access points (APs) to enhance spectral and energy efficiency. The architecture employs distributed beamforming, where both SIM coefficients and local receiver combiner vectors are optimized based on local channel state information (CSI). A low-complexity layer-by-layer iterative optimization algorithm is proposed to maximize the equivalent gain of the channel from users to APs. At the central processing unit (CPU), the weight vector for combining local detections is designed based on the minimum mean square error (MMSE) criterion, taking into account hardware impairments (HWIs). Simulation results show that the SIM-based HMIMO outperforms conventional single-layer HMIMO in terms of achievable rate. The paper also highlights that HWIs at APs and UEs limit the achievable rate in high signal-to-noise-ratio (SNR) regions. The proposed architecture leverages stacked SIMs to achieve higher spatial-domain gain and beamformer degrees of freedom. The SIM-based beamformer operates directly in the native electromagnetic (EM) wave regime without a digital beamformer, enabling simplified hardware architecture and improved computational efficiency. The paper also discusses the application of SIMs in interference cancellation and integrated sensing and communications. The proposed SIM-aided HMIMO architecture is compared with existing MIMO technologies in terms of performance, complexity, and hardware requirements. The paper concludes that the SIM-based HMIMO architecture achieves higher energy efficiency and better performance in cell-free networks, while considering realistic hardware impairments.This paper proposes a stacked intelligent metasurface (SIM)-aided holographic MIMO (HMIMO) architecture for the uplink of cell-free networks. The SIM is deployed at access points (APs) to enhance spectral and energy efficiency. The architecture employs distributed beamforming, where both SIM coefficients and local receiver combiner vectors are optimized based on local channel state information (CSI). A low-complexity layer-by-layer iterative optimization algorithm is proposed to maximize the equivalent gain of the channel from users to APs. At the central processing unit (CPU), the weight vector for combining local detections is designed based on the minimum mean square error (MMSE) criterion, taking into account hardware impairments (HWIs). Simulation results show that the SIM-based HMIMO outperforms conventional single-layer HMIMO in terms of achievable rate. The paper also highlights that HWIs at APs and UEs limit the achievable rate in high signal-to-noise-ratio (SNR) regions. The proposed architecture leverages stacked SIMs to achieve higher spatial-domain gain and beamformer degrees of freedom. The SIM-based beamformer operates directly in the native electromagnetic (EM) wave regime without a digital beamformer, enabling simplified hardware architecture and improved computational efficiency. The paper also discusses the application of SIMs in interference cancellation and integrated sensing and communications. The proposed SIM-aided HMIMO architecture is compared with existing MIMO technologies in terms of performance, complexity, and hardware requirements. The paper concludes that the SIM-based HMIMO architecture achieves higher energy efficiency and better performance in cell-free networks, while considering realistic hardware impairments.