Abstract
This article presents Kadabra, a Java source-to-source compiler that allows users to make code queries, code analysis and code transformations, all user-programmable using the domain-specific language LARA. We show how Kadabra can be used as the basis for developing a runtime autotuning and adaptivity framework, able to adapt existing source Java code in order to take advantage of runtime autotuning. Specifically, this article presents the framework, consisting of Kadabra and an API for runtime adaptivity. We show the use of the framework to extend Java applications with autotuning and runtime adaptivity mechanisms to target performance improvement and/or energy saving goals.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Abstract
[No abstract available]

Abstract
A common approach for improving performance uses FPGAs to accelerate critical code regions, which often involves two processes: hardware/software partitioning, which identifies regions to offload to the FPGA; and optimizing those regions (e.g., through HLS directives). As both processes are separate and usually applied in sequence, the interplay between them is unnatural, and it is unclear how the choices made in one step can benefit the choices made in the other step. This paper presents our work-in-progress for combining partitioning and optimization into a single holistic process. First, our source-to-source compiler builds a task-based representation from the input application. Then, a greedy algorithm builds clusters of tasks and assigns each cluster to either hardware (FPGA) or software (CPU). The algorithm iteratively refines the clusters and offloading decisions by: a) minimizing the communication costs between clusters by assigning tasks that work with shared data to the same cluster; b) reducing the global execution time by applying code optimizations to the tasks in each cluster. We show the impact of our holistic approach to a motivating edge detection example and compare the results when applying partitioning and code optimizations as independent steps. The results show that a holistic partitioning can lead to a speedup of up to 28.7x when compared to a simple offloading of the application to an FPGA.

Abstract
Haptic feedback in Virtual Reality is commonly provided through wearable or grounded devices adapted to specific scenarios and situations. Shape-changing devices allow for the physical representation of different virtual objects but are still a minority, complex, and usually have long transformation times. We present Shape-a-getti, a novel ungrounded, non-wearable, and graspable haptic device that can quickly change between different radially symmetrical shapes. It uses a single actuator to rotate several identical poles distributed along a radius to render the different shapes. The format of the poles defines the possible shapes, and in our prototype, we used one that could render concave, straight, and convex shapes with different radii. We conducted a user evaluation with 21 participants asking them to recognize virtual objects by grasping the Shape-a-getti. Despite having difficulties distinguishing between some objects with very similar shapes, participants could successfully identify virtual objects with different shapes rendered by our device. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Abstract
Virtual reality (VR) has the potential to significantly boost productivity in professional settings, especially those that can benefit from immersive environments that allow a better and more thorough way of visualizing information. However, the physical demands of mid-air movements make it difficult to use VR for extended periods. DeskVR offers a solution that allows users to engage in VR while seated at a desk, minimizing physical exhaustion. However, developing appropriate motion techniques for this context is challenging due to limited mobility and space constraints. This work focuses on object manipulation techniques, exploring touch-based and mid-air-based approaches to design a suitable solution for DeskVR, hypothesizing that touch-based object manipulation techniques could be as effective as mid-air object manipulation in a DeskVR scenario while less physically demanding. Thus, we propose Scaled Indirect Touch 6-DOF (SIT6), an indirect touch-based object manipulation technique incorporating scaled input mapping to address precision and out-of-reach manipulation issues. The implementation of our solution consists of a state machine with error-handling mechanisms and visual indicators to enhance interaction. User experiments were conducted to compare the SIT6 technique with a baseline mid-air approach, revealing comparable effectiveness while demanding less physical exertion. These results validated our hypothesis and established SIT6 as a viable option for object manipulation in DeskVR scenarios. (c) 2023 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Abstract
DeskVR allows users to experience Virtual Reality (VR) while sitting at a desk without requiring extensive movements. This makes it better suited for professional work environments where productivity over extended periods is essential. However, tasks that typically resort to mid-air gestures might not be suitable for DeskVR. In this paper, we focus on the fundamental task of object selection. We present TouchRay, an object selection technique conceived specifically for DeskVR that enables users to select objects at any distance while resting their hands on the desk. It also allows selecting objects' sub-components by traversing their corresponding hierarchical trees. We conducted a user evaluation comparing TouchRay against state-of-the-art techniques targeted at traditional VR. Results revealed that participants could successfully select objects in different settings, with consistent times and on par with the baseline techniques in complex tasks, without requiring mid-air gestures.