The processing-using-memory (PUM; a.k.a. inmemory computing) paradigm aims to eliminate data movement energy and performance costs by using memory cell interactions to directly perform computation. Given PUM's potential for large savings, prior works have proposed many different datapath microarchitectures to demonstrate how general-purpose PUM benefits a wide range of application kernels. Unfortunately, these efforts largely depend on microarchitecture-specific vector-like interfaces that (1) force many of an application's operations to be offloaded to a CPU, (2) require significant programmer effort to scale up applications to an entire memory chip, and (3) make it impractical to develop badly-needed systems software and programming tools for PUM. To address these three issues, we propose the memory processing unit (MPU), a microarchitecture-agnostic interface layer for general-purpose PUM with three components. First, we develop an MPU instruction set architecture (ISA) with instructions to facilitate application scaling and task coordination. Second, we propose an ensemble execution model that coordinates execution across millions of PUM vector function units and maps to most general-purpose PUM microarchitectures. Third, we design a comprehensive MPU control path that efficiently executes MPU ISA binaries across multiple ensembles, and can enable CPU-free execution of complex end-to-end applications with PUM. We demonstrate how the MPU maps to multiple previously-proposed PUM datapaths, and how it achieves average performance/energy improvements of$\mathbf{1. 7 9} \times \boldsymbol{/} \mathbf{3. 2 3} \times$for$\mathbf{2 1}$data-intensive kernels over these prior works ($67 \times / 47 \times$vs. a modern GPU), while also achieving performance and energy improvements for the complex end-to-end applications.

Sandplay is an effective psychotherapy for mental retreatment, and many people prefer to engage in sandplay in Virtual Reality (VR) due to its convenience. Haptic perception of physical objects and miniatures enhances the realism and immersion in VR. Previous studies have rendered sizes by exerting pressure on the user’s fingertips or employing tangible, shape-changing devices. However, these interfaces are limited by the physical shapes they can assume, making it difficult to simulate objects that grow larger or smaller than the interface. Motivated by literature on visual-haptic illusions, this work aims to convey the haptic sensation of a virtual object’s shape to the user by exploring the relationships between the haptic feedback from real objects and their visual renderings in VR. Our study focuses on the confirmation and adjustment ratios for different virtual object sizes. The results show that the likelihood of participants confirming the correct size of virtual cubes decreases as the object size increases, requiring more adjustments for larger objects. This research provides valuable insights into the relationships between haptic sensations and visual inputs, contributing to the understanding of visual-haptic illusions in VR environments.