Related papers: Pipeline Automation Framework for Reusable High-th…
Data pre-processing pipelines are the bread and butter of any successful AI project. We introduce a novel programming model for pipelines in a data lakehouse, allowing users to interact declaratively with assets in object storage. Motivated…
The ability to extract value from historical data is essential for enterprise decision-making. However, much of this information remains inaccessible within large legacy file systems that lack structured organization and semantic indexing,…
High-level synthesis (HLS) has received significant attention in recent years, improving programmability for FPGAs. PolyMage is a domain-specific language (DSL) for image processing pipelines that also has a HLS backend to translate the…
User association, the problem of assigning each user device to a suitable base station, is increasingly crucial as wireless networks become denser and serve more users with diverse service demands. The joint optimization of user association…
Domain-specific accelerators deliver exceptional performance on their target workloads through fabrication-time orchestrated datapaths. However, such specialized architectures often exhibit performance fragility when exposed to new kernels…
Spatially partitioned heterogeneous accelerators (HAs) are increasingly adopted in embedded systems for their performance and flexibility. Yet most existing HA design frameworks optimize primarily for throughput or quality-of-service (QoS)…
The increasing complexity of large-scale FPGA accelerators poses significant challenges in achieving high performance while maintaining design productivity. High-level synthesis (HLS) has been adopted as a solution, but the mismatch between…
Development of modern integrated circuit technologies makes it feasible to develop cheaper, faster and smaller special purpose signal processing function circuits. Digital Signal processing functions are generally implemented either on…
The core challenge in applying abstract interpretation lies in the configuration of abstraction and analysis strategies encoded by a large number of external parameters of static analysis tools. To attain low false-positive rates (i.e.,…
The large communication and computation overhead of federated learning (FL) is one of the main challenges facing its practical deployment over resource-constrained clients and systems. In this work, SpaFL: a communication-efficient FL…
Traditionally, the data plane has been designed with fixed functions to forward packets using a small set of protocols. This closed-design paradigm has limited the capability of the switches to proprietary implementations which are…
DAPHNE is a new open-source software infrastructure designed to address the increasing demands of integrated data analysis (IDA) pipelines, comprising data management (DM), high performance computing (HPC), and machine learning (ML)…
Automated Machine Learning (AutoML) has significantly advanced the efficiency of ML-focused software development by automating hyperparameter optimization and pipeline construction, reducing the need for manual intervention. Quantum Machine…
During the concept design of complex networked systems, concept developers have to ensure that the choice of hardware modules and the topology of the target platform will provide adequate resources to support the needs of the application.…
High-level synthesis (HLS) has enabled the rapid development of custom hardware circuits for many software applications. However, developing high-performance hardware circuits using HLS is still a non-trivial task requiring expertise in…
In most PUF-based authentication schemes, a central server is usually engaged to verify the response of the device's PUF to challenge bit-streams. However, the server availability may be intermittent in practice. To tackle such an issue,…
Reconfigurable-antenna systems have received increasing attention for their ability to adapt wireless channels. However, existing architectures exhibit scenario-dependent limitations: fluid antennas provide strong diversity gains in…
Mapping applications onto heterogeneous platforms is a difficult challenge, even for simple application patterns such as pipeline graphs. The problem is even more complex when processors are subject to failure during the execution of the…
Advanced Driver-Assistance Systems (ADAS) is one of the primary drivers behind increasing levels of autonomy, driving comfort in this age of connected mobility. However, the performance of such systems is a function of execution rate which…
FPGAs (Field Programmable Gate arrays) have gained massive popularity today as accelerators for a variety of workloads, including big data analytics, and parallel and distributed computing. This has fueled the study of mechanisms to…