RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model

Inspired by the recent success of large language models (LLMs) like ChatGPT, researchers start to explore the adoption of LLMs for agile hardware design, such as generating design RTL based on natural-language instructions. However, in existing works, their target designs are all relatively simple and in a small scale, and proposed by the authors themselves, making a fair comparison among different LLM solutions challenging. In addition, many prior works only focus on the design correctness, without evaluating the design qualities of generated design RTL. In this work, we propose an open-source benchmark named RTLLM, for generating design RTL with natural language instructions. To systematically evaluate the auto-generated design RTL, we summarized three progressive goals, named syntax goal, functionality goal, and design quality goal. This benchmark can automatically provide a quantitative evaluation of any given LLM-based solution. Furthermore, we propose an easy-to-use yet surprisingly effective prompt engineering technique named self-planning, which proves to significantly boost the performance of GPT-3.5 in our proposed benchmark

Direct detection of dark photon dark matter using radio telescopes

Dark photons can be the ultralight dark matter candidate, interacting with Standard Model particles via kinetic mixing. We propose to search for ultralight dark photon dark matter (DPDM) through the local absorption at different radio telescopes. The local DPDM can induce harmonic oscillations of electrons inside the antenna of radio telescopes. It leads to a monochromatic radio signal and can be recorded by telescope receivers. Using the observation data from the FAST telescope, the upper limit on the kinetic mixing can already reach $10^{-12}$ for DPDM oscillation frequencies at $1-1.5$ GHz, which is stronger than the cosmic microwave background constraint by about one order of magnitude. Furthermore, large-scale interferometric arrays like LOFAR and SKA1 telescopes can achieve extraordinary sensitivities for direct DPDM search from 10 MHz to 10 GHz.Comment: 5 pages, 3 figures + appendix. Match the accepted version (PRL

Comparison of three methods for the methylation of aliphatic and aromatic compounds

Rationale: Methylation protocols commonly call for acidic, hot conditions that are known to promote organic ^1H/^2H exchange in aromatic and aliphatic C—H bonds. Here we tested two such commonly-used methods and compared a third that avoids these acidic conditions, to quantify isotope effects with each method and to directly determine acidic-exchange rates relevant to experimental conditions. Methods: We compared acidic and non-acidic methylation approaches catalyzed by hydrochloric acid, acetyl chloride and EDCI (1-ethyl-3-(3-dimethylaminopropyl)carbodiimide) / DMAP (4-dimethylaminopyridine) respectively. These were applied to two analytes: phthalic acid (an aromatic) and octacosanoic acid (an aliphatic). We analyzed yield by gas chromatography flame ionization (GC/FID) and hydrogen and carbon isotopic composition by isotope ratio mass spectrometry (GC/IRMS). We quantified the ^1H/^2H exchange rate on dimethyl phthalate under acidic conditions with proton nuclear magnetic resonance (^1H-NMR) measurements. Results: The δ^2H and δ^(13)C values and yield were equivalent among the three methods for methyl octacosanoate. The two acidic methods resulted in comparable yield and isotopic composition of dimethyl phthalate; however, the non-acidic method resulted in lower δ^2H and δ^(13)C values perhaps due to low yields. Concerns over acid-catalyzed ^1H/^2H exchange are unwarranted as the effect was trivial over a 12-hour reaction time. Conclusions: We find product isolation yield and evaporation to be the main concerns in the accurate determination of isotopic composition. ^1H/^2H exchange reactions are too slow to cause measurable isotope fractionation over the typical duration and reaction conditions used in methylation. Thus, we are able to recommend continued use of acidic catalysts in such methylation reactions for both aliphatic and aromatic compounds

MasterRTL: A Pre-Synthesis PPA Estimation Framework for Any RTL Design

In modern VLSI design flow, the register-transfer level (RTL) stage is a critical point, where designers define precise design behavior with hardware description languages (HDLs) like Verilog. Since the RTL design is in the format of HDL code, the standard way to evaluate its quality requires time-consuming subsequent synthesis steps with EDA tools. This time-consuming process significantly impedes design optimization at the early RTL stage. Despite the emergence of some recent ML-based solutions, they fail to maintain high accuracy for any given RTL design. In this work, we propose an innovative pre-synthesis PPA estimation framework named MasterRTL. It first converts the HDL code to a new bit-level design representation named the simple operator graph (SOG). By only adopting single-bit simple operators, this SOG proves to be a general representation that unifies different design types and styles. The SOG is also more similar to the target gate-level netlist, reducing the gap between RTL representation and netlist. In addition to the new SOG representation, MasterRTL proposes new ML methods for the RTL-stage modeling of timing, power, and area separately. Compared with state-of-the-art solutions, the experiment on a comprehensive dataset with 90 different designs shows accuracy improvement by 0.33, 0.22, and 0.15 in correlation for total negative slack (TNS), worst negative slack (WNS), and power, respectively.Comment: To be published in the Proceedings of 42nd IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 202

Monitoring of postoperative neutrophil-to-lymphocyte ratio, D-dimer, and CA153 in: Diagnostic value for recurrent and metastatic breast cancer

ObjectiveThis stydy aims to assess the value of monitoring of postoperative neutrophil-to-lymphocyte ratio (NLR), D-dimer, and carbohydrate antigen 153 (CA153) for diagnosis of breast cancer (BC) recurrence and metastasis.Materials/MethodsA cohort of 252 BC patients who underwent surgery at the First Affiliated Hospital of Anhui Medical University between August 2008 and August 2018 were enrolled in this retrospective study. All patients were examined during outpatient follow-ups every 3 months for 5 years postoperation and every 6 months thereafter. Recurrence or metastasis was recorded for 131 patients but not for the remaining 121. Retrospective analysis of hematological parameters and clinicopathological characteristics allowed comparison between the two groups and evaluation of these parameters for the recurrent and metastatic patients.ResultsLymph node metastasis, higher tumor node metastasis (TNM) staging, and higher histological grade correlated with BC recurrence and metastasis (p < 0.05). Statistical differences were found in absolute neutrophil count (ANC), absolute lymphocyte count (ALC), CEA, CA153, D-dimer, NLR, platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) between the recurrent and metastatic and control groups (p < 0.05). Logistic regression analysis showed that CA153, D-dimer, NLR, and TNM staging were risk factors for BC recurrence and metastasis (p < 0.05). Combined values for the NLR, D-dimer, and CA153 had good diagnostic values, giving the highest area under the curve (AUC) of 0.913. High NLR, D-dimer, and CA153 values were significantly associated with recurrence and metastasis at multiple sites, lymph node metastasis, and higher TNM staging (p < 0.05). Patients with high CA153 were more likely to have bone metastases (p < 0.05), and those with high D-dimer were prone to lung metastasis (p < 0.05). With the increasing length of the postoperative period, the possibility of liver metastases gradually decreased, while that of chest wall recurrence gradually increased (p < 0.05).ConclusionMonitoring postoperative NLR, D-dimer, and CA153 is a convenient, practical method for diagnosing BC recurrence and metastasis. These metrics have good predictive value in terms of sites of recurrence and metastasis and the likelihood of multiple metastases