Recent advancements in hardware and software systems have been driven by the
deployment of emerging smart health and mobility applications. These developments have …

In this work, we present a C ompiler-integrated, E xtensible D omain Specific System on
Chip R untime (CEDR) ecosystem to facilitate research toward addressing the challenges of …

EASE: Energy Optimization through Adaptation – A Review of Runtime Energy-Aware
Approximate Deep Learning Algorithms Page 1 P osted on 6 F eb 2024 — CC-BY 4.0 — h …

RISC-V based architectures have gained attention for deployment on platforms from SoC to
HPC scale to meet the demands of a wide range of computational workloads that may …

As the landscape of computing advances, system designers are increasingly exploring
methodologies that leverage higher levels of heterogeneity to enhance performance within …

In this study, we introduce a methodology for automatically transforming user applications
written in C/C++ to a parallel representation consisting of coarse-grained tasks based on …

Viterbi decoders are widely used in communication systems, natural language processing
(NLP), and other domains. While Viterbi decoders are compute-intensive and power-hungry …

This paper summarizes the talks of a special session on the IPF 2.0 project, a collaborative
German-US research project that leverages self-awareness principles for the self …

With technological developments, the resolution of the display systems is increasing,
causing image data to increase. Several technologies are aiding in optimizing these data …

Simultaneous multithreading (SMT) improves the performance of superscalar CPUs by
exploiting thread-level parallelism with shared entries for better utilization of resources. A …