Search Results for "cpu performance meter" - Page 17

MRTG-PME is a set of performance monitoring extensions to MRTG that allow historical graphing of OS performance data (CPU, memory, paging, disk, etc.) for Linux, Solaris and BSD. With no SNMP required, PME is arguably more secure than standard MRTG.

Uechi APM Web is an APM (Application Performance Management) Open Source Server Performance Monitor written and developed in Java and C # for all Linux and Windows platforms. The Uechi.APM.Web offers a complete resource for unlimited monitoring servers in real time. Have full control of the CPU consumption, memory, disk and network traffic. Communication is done via TCP Protocol Socket connection.

Dia-1.6B is a 1.6 billion parameter text-to-speech model by Nari Labs that generates high-fidelity dialogue directly from transcripts. Designed for realistic vocal performance, Dia supports expressive features like emotion, tone control, and non-verbal cues such as laughter, coughing, or sighs. The model accepts speaker conditioning through audio prompts, allowing limited voice cloning and speaker consistency across generations. It is optimized for English and built for real-time performance on enterprise GPUs, though CPU and quantized versions are planned. ...

Indus OS is a super lightweight, secure and modern Debian-based Linux operating system proudly made in India. It is specially designed for users switching from Windows 10, offering a familiar Windows 10 style interface through the Indus Desktop Environment (based on XFCE). The desktop looks and feels similar to Windows 10, making the transition smooth and comfortable for beginners while still remaining powerful for advanced users. Key highlights: • Windows 10 inspired user...

granite-timeseries-ttm-r2 is part of IBM’s TinyTimeMixers (TTM) series—compact, pre-trained models for multivariate time series forecasting. Unlike massive foundation models, TTM models are designed to be lightweight yet powerful, with only ~805K parameters, enabling high performance even on CPU or single-GPU machines. The r2 version is pre-trained on ~700M samples (r2.1 expands to ~1B), delivering up to 15% better accuracy than the r1 version. TTM supports both zero-shot and fine-tuned forecasting, handling minutely, hourly, daily, and weekly resolutions. It can integrate exogenous variables, static categorical features, and perform channel-mixing for richer multivariate forecasting. ...