Search Results for "throughput"

An open-source free cross-platform multi-protocol VPN program, as an academic project from University of Tsukuba, under the Apache License 2.0. The API Suite allows you to easily develop your original SoftEther VPN Server management application to control the VPN Server (e.g. creating users, adding Virtual Hubs, disconnecting a specified VPN sessions) from JavaScript, TypeScript, C# or other languages. SoftEther VPN ("SoftEther" means "Software Ethernet") is one of the world's most powerful...

qvac-fabric-llm.cpp is a cross-platform large language model inference and fine-tuning engine built as an advanced fork of llama.cpp, designed to run efficiently across desktops, mobile devices, and heterogeneous GPU environments. The project focuses on removing hardware limitations traditionally associated with LLM deployment by enabling support for a wide range of backends, including Vulkan, Metal, CUDA, and CPU, making it accessible on devices ranging from smartphones to enterprise...

Iperf here is a means of measuring networks - capacity & latency (including ECN) over sockets both TCP and UDP. The goals include maintaining an active iperf code base across a broad set of platforms and operating systems. This is a multi-threaded design that scales with the number of CPUs or cores within a system. It supports both high impact and low impact techniques to obtain and report network performance. Current release: 2.2.1, Nov 4th, 2024 About iperf 2 and iperf3: Read...

...The repository targets practitioners who want to keep familiar PyTorch modeling while preparing models for Core ML/ANE execution paths. Documentation highlights reported improvements in throughput and memory residency, while releases track incremental fixes and packaging updates. The project sits alongside related Apple ML repos that focus on deploying attention-based models efficiently to ANE-equipped hardware. In short, it’s a practical blueprint for adapting Transformers to Apple’s dedicated ML accelerator without rewriting entire model stacks.