Cryo-electron microscopy (cryo-EM) is a key technique for structural biology, but its computational efficiency, particularly during 3D reconstruction, remains a bottleneck. We introduce T2-RELION, a highly optimized version of RELION for cryo-EM 3D reconstruction on CPU-GPU platforms. RELION is a widely used open-source package in the cryo-EM community. We identify and resolve key inefficiencies in RELION’s parallelization strategy and memory management by proposing task parallelism and a three-phase GPU memory management strategy. Furthermore, we leverage Tensor Cores to accelerate the hot-spot kernel for difference calculation, employing an advanced pipelining strategy to hide latency and enable thread-block-level data reuse. On a quad-A100 GPU machine, performance evaluations demonstrate that T2-RELION outperforms RELION 4.0. For the hot-spot kernel, our optimizations achieve 1.90-23.7 times speedup. For the whole application using CNG and Trpv1 datasets, we observe 3.86 times and 2.68 times speedups, respectively.

Deformable object manipulation is a challenging problem due to its complex deformable properties. With the development of artificial intelligence, learning-based methods have shown outstanding performance in robotic manipulation. Previous works have investigated the manipulation of deformable objects via Reinforcement Learning (RL) in simulation. However, they approximate object deformation with particles, using particle states as observations, which are unavailable in reality. To address these issues, we utilize Vision-Based Tactile Sensors (VBTSs) as the end-effector to manipulate and observe the deformable objects. In this work, we develop a new contact simulation environment for deformable objects, including elastic, plastic, and elastoplastic. We utilize RL strategies and expert demonstrations to train agents in the simulation. Finally, we build a real experimental platform to complete the sim-to-real tasks and robustness testing. Our work introduces an innovative strategy that utilizes high-resolution VBTSs for contact simulation and manipulation of deformable objects. The experimental results show superior performances of deformable object manipulation with the proposed method.