Search Results for "overclock cpu intel"
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Showing 59 open source projects for "overclock cpu intel"
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AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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Loan management software that makes it easy.Bryt Software is ideal for lending professionals who are looking for a feature rich loan management system that is intuitive and easy to use. We are 100% cloud-based, software as a service. We believe in providing our customers with fair and honest pricing. Our monthly fees are based on your number of users and we have a minimal implementation charge.
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Intel PCM
Intel® Performance Counter Monitor (Intel® PCM)
Intel® Performance Counter Monitor (Intel® PCM) is an application programming interface (API) and a set of tools based on the API to monitor performance and energy metrics of Intel® Core™, Xeon®, Atom™ and Xeon Phi™ processors. PCM works on Linux, Windows, Mac OS X, FreeBSD, DragonFlyBSD and ChromeOS operating systems. -
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FastSD CPU
Fast stable diffusion on CPU and AI PC
...The repository contains multiple interfaces including a desktop GUI for simple generation, an advanced web-based UI with support for extensions like LoRA and ControlNet, and a command-line interface for scripted usage or server deployments. With support for performance-oriented libraries such as OpenVINO and hardware acceleration on platforms like Intel AI PCs, FastSD CPU aims to shrink generation times dramatically compared with naive CPU implementations. -
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Likwid
Performance monitoring and benchmarking suite
Likwid is a simple to install and use toolsuite of command line applications and a library for performance oriented programmers. It works for Intel, AMD, ARMv8 and POWER9 processors on the Linux operating system. There is additional support for Nvidia and AMD GPUs. There is support for ARMv7 and POWER8/9 but there is currently no test machine in our hands to test them properly. -
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auto-cpufreq
Automatic CPU speed & power optimizer for Linux
Automatic CPU speed & power optimizer for Linux. Actively monitors laptop battery state, CPU usage, CPU temperature, and system load, ultimately allowing you to improve battery life without making any compromises. -
Failed Payment Recovery for Subscription BusinessesFlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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GameMode
Optimise Linux system performance on demand
GameMode is a daemon/lib combo for Linux that allows games to request a set of optimizations be temporarily applied to the host OS and/or a game process. GameMode was designed primarily as a stop-gap solution to problems with the Intel and AMD CPU power save or on-demand governors but is now host to a range of optimization features and configurations. -
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OpenVINO
OpenVINO™ Toolkit repository
...Boost deep learning performance in computer vision, automatic speech recognition, natural language processing and other common tasks. Use models trained with popular frameworks like TensorFlow, PyTorch and more. Reduce resource demands and efficiently deploy on a range of Intel® platforms from edge to cloud. This open-source version includes several components: namely Model Optimizer, OpenVINO™ Runtime, Post-Training Optimization Tool, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi. -
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CTranslate2
Fast inference engine for Transformer models
...The project supports x86-64 and AArch64/ARM64 processors and integrates multiple backends that are optimized for these platforms: Intel MKL, oneDNN, OpenBLAS, Ruy, and Apple Accelerate. -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. ... -
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AutomatedLab
Framework that lets you deploy complex labs on HyperV and Azure
...There are only two requirements you need to make sure: You need the DVD ISO images and a Hyper-V host or an Azure subscription. Requires Windows Management Framework 5+ (Windows). Requires Intel VT-x or AMD/V capable CPU, a decent amount of RAM, and low-latency high-throughput storage (No spinning disks please, as there are issues related to them). This solution supports setting up virtual machines with Windows 7, 2008 R2, 8 / 8.1 and 2012 / 2012 R2, 10 / 2016, 2019, and SQL Server 2008, 2008R2, 2012, 2014, 2016, 2017, 2019. -
Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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OpenFace Face Recognition
Face recognition with deep neural networks
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google, Vodafone, NVIDIA, and the Conklin Kistler family fund. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and should not be attributed to their employers or funding sources. ... -
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LinuxHardware Info
Hardware Info for Linux portable AppImage + Benchmark
LinuxHardware Info (portable/AppImage) -------------------------------------- Ihr wollt wissen was in Eurem Rechner steckt? Genau das könnt Ihr mit LinuxHardwareInfo, ohne jedes mal die Konsole zu bemühen. Kurz-Info: - Hardware Analyse - einfache Benchmarks (CPU / Grafik/RAM und HDD) - HDD/USB Fake Erkennung - Live Sensoren - Portable AppImage (einfach vom USB-Stick in Live-Image kopieren) - automatische Update Erkennung ab v1.2 - Darkmode - und anderes - im Support-Forum gibt... -
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Prime number ( primenumbers )
Benchmark for 50 000 000 prime numbers as single and multicore
Simple source files and compiled JAR Java programs, for benchmark 50 000 000 cycle finding prime numbers. On Intel(R) Core(TM) i5-8600K CPU, Windows 10 20H2, i have 39 second on single core and 7,6 second on multi core. (PS: C++ multicore 6 second). Added C files for gcc compiler in Windows 10 and for Xcode C command line project in MacOS ( tested on Mac mini M2 with single core 16 to 25 sec and multicore 2,3 to 5 second by compiler -O switch). -
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This is a freedom software and it obeys opensource initiative. The main purpose of this project is to bring extra updates to the existing Octave OCL project with more supporting PC devices like Intel GPU, AMD APUs, and Apple Silicon GPU as well as mobile devices like Qualcomm Adreno and ARM Mali GPUs. Due to the fact tremendous time and energy has been spent on its working on many devices, the project name is changing to AnyArray to reflect it is really working on many devices in 9 March...
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... ⚡ Key Features: • Super lightweight ISO (263MB) • Fast boot and low memory footprint • Clean, minimal user interface • Pre-installed basic tools: file manager, text editor, terminal, and more • Perfect for reviving old PCs or running in lightweight virtual environments 🖥️ Minimum System Requirements: • CPU: Intel Pentium II / AMD K6-2 or newer (32-bit) • RAM: 256 MB minimum • Storage: 400 MB free disk space Website: xxri.rf.gd Maintained by: xxri OS Team
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LDPartEditor
Create and edit LDraw™ parts quick and easy.
...Minimum System Requirements: - OpenGL 2.1 compatible Graphics Card - Operating System (64-bit): Windows [7 or newer], Mac OS X [>=14], Linux [e.g. Linux Mint >=22] - CPU: Multicore-Processor e.g. Intel Core 2 Duo or AMD Athlon II (>2.0Ghz) - RAM: 4 GB - Video-Memory: 1 GB - Free Disk Space: 150 MB Recommended Requirements: - OpenGL 3.3 compatible Graphics Card - Operating System (64-bit): Windows 7,8,10,11, Mac OS X [>=14], Linux [e.g. Linux Mint >=22] - CPU: Multicore-Processor with 4 cores (or more) - RAM: >4 GB - Video-Memory: >1 GB - Free Disk Space: 512 MB The sourcecode is now hosted on GitHub here: http://nilsschmidt1337.github.io/ldparteditor/ -
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PI-Based Image Encoder / Converter
Python code able to convert / compress image to PI (3.14, π) Indexes
...ZIP also include 16 MB file with 16,7 mil numbers of PI Benchmark(Single-Thread): Hardware & Environment Apple Silicon: Apple M2 (Mac mini/MacBook) x86_64 Platform: Intel Core Ultra 5 225F (Arrow Lake, 10 Cores) OS 1: Fedora 43 (GNOME) OS 2: Windows 11 Pro (23H2/24H2) Software: Python 3.14.3 + Numba JIT (latest) Results (Lower is better) Platform / OS CPU Time (Seconds) macOS (Native) Apple M2 52.151311 s (in default setup) Fedora Linux Intel Core Ultra 5 225F 58.536457 s (in default Power Management: Balanced) Windows 11 Intel Core Ultra 5 225F 59.681427 s (important! ... -
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Internet Friendly Media Encoder
Simple, Flexible & Powerful H.265/HEVC & H266/VVC video encoder!
...The software also supports AviSynth for advanced video processing. The video and audio encoders are implemented in a plug-in style, enabling users to add their own compiled, optimized CPU architectures for increased speed. This modular design ensures that the encoder remains adaptable and expandable, allowing for the addition of new and future encoding technologies. Internet Friendly Media Encoder also supports hardware acceleration from Intel, AMD, and NVidia for encoding in H264, H265, and AV1 formats. -
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sdcc-z80n-mingw64-binaries
A z80n-targeted repack of SDCC Win64 snapshot
This is a z80n-targeted repackaged snapshot of a Win64 build of SDCC - free open source, retargettable, optimizing ISO C compiler ( https://sdcc.sourceforge.net/ ) "Free open source, retargettable, optimizing ISO C compiler suite that targets a growing list of processors including the Intel MCS-51 based (8031, 8032, 8051, 8052, etc.), Maxim (formerly Dallas) DS80C390 variants, Freescale (formerly Motorola) HC08 based (hc08, s08), Zilog Z80 based MCUs (Z80, Z80N, Z180, SM83 (e.g. Game... -
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Tria Sistema Operatiu
Helps you find, download & burn the best Operating System for any PC
Tria O.S. detects hard & soft specs of the PC where you run it, you can load this info or specify it manually to let the program inform you what would be the best operating system for a specific PC, with the specified hardware, and then see the difference by adding RAM, a SSD hard drive, changing the graphics card ... etc. REQUIREMENTS: For Linux, you need GAMBAS 3.3 or later, so you will have to install the gambas3 package before installing. 90's EDITION needs 160 MB (192 MB on... -
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No for upload testing rom
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Powerlimit
Set Power Limits and Voltage Offsets for Intel CPUs on Linux
With Powerlimit you can set all the properties of the Power Limits on modern Intel CPUs (>= 6th generation). You can enable and disabled the Long and Short Term Limits, set the Wattage and the Time Window, or enable and disabled Clamping. Additionally, you are able to set Power Limits for Cores, Graphics and DRAM, if your CPU supports this. Moreover, to reduce the power consumption of your CPU you can define voltage offsets for your Core, Cache, Uncore, Graphics and IO voltages. ... -
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Throttled
Workaround for Intel throttling issues in Linux
This tool was originally developed to fix Linux CPU throttling issues affecting Lenovo T480 / T480s / X1C6. The CPU package power limit (PL1/2) is forced to a value of 44 W (29 W on battery) and the temperature trip point to 95 'C (85 'C on battery) by overriding default values in MSR and MCHBAR every 5 seconds (30 on battery) to block the Embedded Controller from resetting these values to default. On systems where the EC doesn't reset the values (ex: ASUS Zenbook UX430UNR), the power limit... -
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GCLinux
Distribuição Linux utilizada no projeto Gênio Cristão
...Como instalar o GCLinux: https://sourceforge.net/p/gclinux/blog/2021/07/como-instalar-o-gclinux-no-disco-r%C3%ADgido-ou-unidade-flash-usb/ REQUISITOS Processador: CPU i686 ou mais recente, todos os processadores Intel e os processadores AMD funcionarão Memória: 128 MB de RAM para desktop 512 MB de RAM para executar o navegador Web -
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SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
...AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. -
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Flashlight library
A C++ standalone library for machine learning
...Flashlight can be broken down into several components as described above. Each component can be incrementally built by specifying the correct build options. Flashlight is most-easily built and installed with vcpkg. Both the CUDA and CPU backends are supported with vcpkg. For either backend, first, install Intel MKL. Flashlight app binaries are also built for the selected features and are installed into the vcpkg install tree's tools directory.
