#c_lang #intel_wireless_devices #iwlwifi #kext #macos

https://github.com/AppleIntelWifi/adapter

#python #amd #bot #docker #intel #nvidia #raspberrypi #rtx3070 #rtx3080 #rtx3090

https://github.com/EricJMarti/inventory-hunter

#c_lang #intel_wifi #itlwm #kernel_extension #kext #macos

https://github.com/OpenIntelWireless/itlwm

#cplusplus #cuda #intel_gpu #rust

https://github.com/vosen/ZLUDA

#c_lang #amd #android #arm #cpus #intel #linux #macos #microarchitecture #windows

https://github.com/Dr-Noob/cpufetch

#c_lang #amd #gpu #intel #linux #macos #ncnn #nvidia #realcugan #vulkan #windows

https://github.com/nihui/realcugan-ncnn-vulkan

#ocaml #intel #introspection #performance_tools #profile #tracing #visualizer #x86

https://github.com/janestreet/magic-trace

#cplusplus #android #deep_learning #deployment #graphcore #intel #ios #jetson #kunlun #object_detection #onnxruntime #openvino #picodet #rockchip #sdk #serving #tensorrt #uie #yolov5

https://github.com/PaddlePaddle/FastDeploy

#c_lang #amd #cpu_cache #cpu_monitoring #cpu_temperature #cpu_topology #cpu_voltage #cpuid #cpuinfo #epyc #intel #multi_core #overclocking #process_monitor #processor #processor_architecture #ram_info #ryzen #threadripper #timings #turbo_boost

https://github.com/cyring/CoreFreq

#cplusplus #addon #amd #av1 #dnxhr #ffmpeg #h264 #h265 #intel #libobs #linux #macos #multiplatform #nvidia #obs #obs_studio #obs_studio_plugin #plugin #prores #vp9 #windows

https://github.com/Xaymar/obs-StreamFX

#python #graphcore #habana #inference #intel #onnx #onnxruntime #optimization #pytorch #quantization #tflite #training #transformers

https://github.com/huggingface/optimum

#cplusplus #4_bits #attention_sink #chatbot #chatpdf #intel_optimized_llamacpp #large_language_model #llm_cpu #llm_inference #smoothquant #sparsegpt #speculative_decoding #stable_diffusion #streamingllm

https://github.com/intel/intel-extension-for-transformers

#cplusplus #amd #dlss #framegeneration #fsr2 #fsr3 #intel #nvidia #tweak #upscaler #xess

OptiScaler is a tool that helps you change how games look by using different upscaling methods like DLSS, FSR, or XeSS. It allows you to replace one method with another in games that already support these technologies. This means you can choose the best option for your computer's hardware, improving performance and visuals. OptiScaler also offers features like frame generation and anti-lag options, making it easier to customize your gaming experience. However, be careful not to use it with online games as it might trigger anti-cheat systems.

https://github.com/cdozdil/OptiScaler

#python #deep_learning #intel #machine_learning #neural_network #pytorch #quantization

Intel Extension for PyTorch boosts the speed of PyTorch on Intel hardware, including both CPUs and GPUs, by using special features like AVX-512, AMX, and XMX for faster calculations[5][2][4]. It supports many popular large language models (LLMs) such as Llama, Qwen, Phi, and DeepSeek, offering optimizations for different data types and easy GPU acceleration. This means you can run advanced AI models much faster and more efficiently on your Intel computer, with simple setup and support for both ready-made and custom models.

https://github.com/intel/intel-extension-for-pytorch