Back to News
Semiconductor Engineering3 July 202618h ago

LLM Agents To Refactor Software For High Level Synthesis (Carnegie Mellon, UCLA)

Researchers from Carnegie Mellon University and UCLA published a technical paper titled “AgRefactor: Self-Evolving Agentic Workflow for HLS Compatibility and Performance.” The paper introduces an “LLM-based multi-agent workflow  for refactoring software into HLS-compatible programs” and reports a 6.51× geometric mean speedup over a state-of-the-art pragma tuning tool. Find the technical paper here

Read Original Article

Related News

Plug-and-play single-photon source can work at room temperature

The Korea Research Institute of Standards and Science (KRISS) has developed a room-temperature single-photon source built into a compact 19-inch rack-mounted device that operates without cryogenic cooling. Designed as a plug-and-play system that works as soon as it is powered on, the device moves quantum light source technology beyond the laboratory and closer to practical, onsite use.

Read More →

Computational Strategies for Schottky Barrier Heights Prediction (NIST, U. Maryland, Johns Hopkins)

Researchers from NIST, University of Maryland, and Johns Hopkins University published a technical paper titled “Effect of Exchange-Correlation Functionals on Schottky Barriers at Si/Metal Interfaces.” Abstract excerpt “Accurate prediction of Schottky barrier heights (SBHs) at metal–semiconductor interfaces is essential for understanding and optimizing charge injection in electronic and optoelectro

Read More →

Probabilistic Memory Architecture That Bridges The Gap Between RNG Sampling and Memory Access (Notre Dame, Georgia Tech, Villanova)

Researchers from University of Notre Dame, Georgia Institute of Technology, and Villanova University published a technical paper titled “Probabilistic Memory for Trustworthy Edge Intelligence.” Summary: The paper introduces p-MEM as “a unified memory primitive” that samples at “the native memory bandwidth.” It reports reductions in instruction count, sampling latency, and energy for Bayesian neura

Read More →