Fast machine code generation is especially important for fast start-up in just-in-time compilation, where the compilation time is part of the end-to-end latency. However, widely used compiler frameworks like LLVM do not prioritize fast compilation and require an extra IR translation step increasing latency even further; and rolling a custom code generator is a large engineering effort, especially when targeting multiple architectures.Therefore, in this paper, we present TPDE, a compiler back-end framework that adapts to existing code representations in SSA form. Using an IR-specific adapter providing canonical access to IR data structures and a specification of the IR semantics, the framework performs one analysis pass and then performs the compilation in just a single pass, combining instruction selection, register allocation, and instruction encoding. The generated target instructions are primarily derived code written in a high-level language through LLVM’s Machine IR, easing portability to different architectures while enabling optimizations during code generation.To show the generality of our framework, we build a new back-end for LLVM from scratch targeting x86-64 and AArch64. Performance results on SPECint 2017 show that we can compile LLVM-IR 8–26x faster than LLVM -O0 while being on-par in terms of run-time performance. We also demonstrate the benefits of adapting to domain-specific IRs in JIT contexts, particularly WebAssembly and database query compilation, where avoiding the extra IR translation further reduces compilation latency.

This work presents an extended version of the Vehicle Energy Dataset (VED), which is a openly released large-scale dataset of vehicle trip energy consumption records. Compared with its original version, the extended VED (eVED) dataset11A description of our eVED dataset can be found at https://github.com/zhangs12013/eVED, and users can download our data and code via git clone https://bitbucket.org/datarepo/eved-dataset.git is enhanced with accurate vehicle trip GPS coordinates. Based on the accurate trip trajectories, we associate the VED trip records with external information that is essential in analyzing vehicle energy consumption e.g., road speed limit and intersections, from open-source map services. Particularly, we calibrate all the GPS trace records in the original VED data, upon which we associated the VED data with external attributes extracted from Geographic Information System (QGIS), the Overpass API, the Open Street Map API, and Google Maps API. The extracted attributes include$12,609,170$records of road elevation, 12,203,044 of speed limit, 12,281,719 of bi-directional speed limit, 584,551 of intersections, 429,638 of bus stop, 312,196 of crossings, 195,856 of traffic signals, 29,397 of stop signs, 5,848 of turning loops, 4,053 of railway crossings, 3,554 of turning circles, and 2,938 of motorway junctions. With the accurate GPS traces and enriched features of the vehicle trip records, the obtained eVED dataset can facilitate research on vehicle energy consumption and energy-efficient approaches, especially machine/deep learning approaches that are demanding on data volume and richness. Moreover, our software work of data calibration and enrichment can be reused to generate further vehicle trip datasets for specific user cases that empower vehicle behavior and traffic dynamic analyses. We anticipate that the eVED dataset and our data enrichment software can serve the academia and industry as an apparatus in developing future vehicle technologies.

Low compilation times are highly important in contexts of Just-in-time compilation. This not only applies to language runtimes for Java, WebAssembly, or JavaScript, but is also crucial for database systems that employ query compilation as the primary measure for achieving high throughput in combination with low query execution time. We present a performance comparison and detailed analysis of the compile times of the JIT compilation back-ends provided by GCC, LLVM, Cranelift, and a single-pass compiler in the context of database queries. Our results show that LLVM achieves the highest execution performance, but can compile substantially faster when tuning for low compilation time. Cranelift achieves a similar run-time performance to unoptimized LLVM, but compiles just 20–35% faster and is outperformed by the single-pass compiler, which compiles code 16x faster than Cranelift at similar execution performance.

Synthetic Biology aims to create biological systems from scratch that do not exist in nature. An important method in this context is the engineering of DNA sequences such that cells realize Boolean functions that serve as control mechanisms in biological systems, e.g. in medical or agricultural applications. Libraries of logic gates exist as predefined gene sequences, based on the genetic mechanism of transcriptional regulation. Each individual gate is composed of different biological parts to allow for the differentiation of their output signals. Even gates of the same logic type therefore exhibit different transfer characteristics, i.e. relation from input to output signals. Thus, simulation of the whole network of genetic gates is needed to determine the performance of a genetic circuit. This makes mapping Boolean functions to these libraries much more complicated compared to EDA. Yet, optimal results are desired in the design phase due to high lab implementation costs. In this work, we identify fundamental features of the transfer characteristic of gates based on transcriptional regulation which is widely used in genetic gate technologies. Based on this, we present novel exact (Branch-and-Bound) and heuristic (Branch-and-Bound, Simulated Annealing) algorithms for the problem of technology mapping of genetic circuits and evaluate them using a prominent gate library. In contrast to state-of-the-art tools, all obtained solutions feature a (near) optimal output performance. Our exact method only explores 6.5 % and the heuristics even 0.2 % of the design space.

In today's digital control rooms, desktop computers represent the most common interface for process control. Compared to their predecessors -- manual control actuators -- desktop computers enable quick and effective process intervention but they lack in process-related interaction qualities such as haptic feedback and the involvement of motor skills. Thus, design trade-offs have to be made to combine the strengths of both paradigms: today's processing power with the interaction qualities of former control room interfaces. In this paper related interaction concepts are presented and evaluated. In a control room scenario, participants were tasked with adjusting numerical values -- so-called process variables -- under two traditional conditions (mouse, keyboard) and two post-WIMP conditions (touch, tangible). Task completion time and recall accuracy of the adjusted values were measured. As a result, traditional desktop interaction proved to be faster, whereas control actions could be recalled significantly better using the tangible control elements. We therefore suggest providing both tangible control for process maintenance and traditional desktop interaction in critical situations that require quick intervention.

Context-sensitive information is of vital importance to the monitoring of processes in control rooms, but its incorporation in current state-of-the-art user interfaces is inadequate. By looking at a traffic control center as an example, this paper proposes an interaction concept for monitoring complex networks on large remote displays. Our approach is based on content-aware navigation with the goal to improve the navigation of the road network and the availability of context-sensitive information. We conducted a study comparing different navigation techniques as well as two techniques for visualizing context-sensitive information.

This paper describes the perspective+detail visualization concept, which extends the conventional overview+detail pattern by adding a perspective viewing area and a further, text-based area containing partial details. Known problems of such extensions are mitigated using a vertically curved display. Our concept aims to bridge both the geographical and the content gap between the two main display areas and to provide an improved overview. An experimental case study based on a typical traffic control room operator task provided first insights on our visualization. These initial findings revealed that perspective+detail assists users in fulfilling their tasks and keeping their orientation in the information space.