Alternatives to OpenCL
Compare OpenCL alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to OpenCL in 2026. Compare features, ratings, user reviews, pricing, and more from OpenCL competitors and alternatives in order to make an informed decision for your business.
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1
SYCL
The Khronos Group
SYCL is an open, royalty-free, cross-platform programming standard defined by the Khronos Group that enables heterogeneous and offload computing in modern ISO C++ by providing a single-source abstraction layer where host and device code coexist in the same C++ source and can target a wide range of devices such as CPUs, GPUs, FPGAs, and other accelerators. It is a C++ API and abstraction designed to make heterogeneous computing more productive and portable by using standard language features such as templates, inheritance, and lambda expressions so developers can write and manage data and execution across diverse hardware without resorting to proprietary languages or extensions. SYCL builds on concepts of underlying acceleration backends like OpenCL and allows integration with other technologies while providing a consistent language, APIs, and ecosystem for locating devices, managing data, and executing kernels. -
2
Assembly
Assembly
Assembly language is a low-level computer programming language that is used to directly control the hardware of a computer system. It consists of symbols and words that represent specific instructions to the processor. Assembly language is often used to optimize programs written in higher-level languages, as it can provide a more efficient way to access memory and other resources. -
3
Mojo
Modular
Mojo 🔥 — a new programming language for all AI developers. Mojo combines the usability of Python with the performance of C, unlocking unparalleled programmability of AI hardware and extensibility of AI models. Write Python or scale all the way down to the metal. Program the multitude of low-level AI hardware. No C++ or CUDA required. Utilize the full power of the hardware, including multiple cores, vector units, and exotic accelerator units, with the world's most advanced compiler and heterogenous runtime. Achieve performance on par with C++ and CUDA without the complexity.Starting Price: Free -
4
oneAPI
Intel
Intel oneAPI is an open, unified programming model designed to simplify development across CPUs, GPUs, and other accelerators. It provides developers with a highly productive software stack for AI, HPC, and accelerated computing workloads. oneAPI supports scalable hybrid parallelism, enabling performance portability across different hardware architectures. The platform includes optimized libraries, SYCL-based C++ extensions, and powerful developer tools for profiling, debugging, and optimization. Developers can build, optimize, and deploy applications with confidence across data centers, edge systems, and PCs. oneAPI is built on open standards to avoid vendor lock-in while maximizing performance. It empowers developers to write code once and run it efficiently everywhere. -
5
NeuroSplit
Skymel
NeuroSplit is a patent-pending adaptive-inferencing technology that dynamically “slices” a model’s neural network connections in real time to create two synchronized sub-models, executing initial layers on the end user’s device and offloading the remainder to cloud GPUs, thereby harnessing idle local compute and reducing server costs by up to 60% without sacrificing performance or accuracy. Integrated into Skymel’s Orchestrator Agent platform, NeuroSplit routes each inference request across devices and clouds based on specified latency, cost, or resource constraints, automatically applying fallback logic and intent-driven model selection to maintain reliability under varying network conditions. Its decentralized architecture ensures end-to-end encryption, role-based access controls, and isolated execution contexts, while real-time analytics dashboards provide insights into cost, throughput, and latency metrics. -
6
CUDA
NVIDIA
CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.Starting Price: Free -
7
F#
F#
F# gives you simplicity and succinctness like Python with correctness, robustness and performance beyond C# or Java. F# is open source, cross-platform and free to use with professional tooling. F# is a JavaScript and .NET language for web, cloud, data-science, apps and more. Cloud computing relies on leveraging multiple integrated services. Using multiple services required a unique set of technologies and capabilities, and F# excels in this domain. With the recent rise of cloud solutions, it is becoming increasingly easy to deploy multiple services “in the cloud”, expanding what is possible both by storing large amounts of data and running heavy computations distributed across clusters of machines.Starting Price: Free -
8
DeepSpeed
Microsoft
DeepSpeed is an open source deep learning optimization library for PyTorch. It's designed to reduce computing power and memory use, and to train large distributed models with better parallelism on existing computer hardware. DeepSpeed is optimized for low latency, high throughput training. DeepSpeed can train DL models with over a hundred billion parameters on the current generation of GPU clusters. It can also train up to 13 billion parameters in a single GPU. DeepSpeed is developed by Microsoft and aims to offer distributed training for large-scale models. It's built on top of PyTorch, which specializes in data parallelism.Starting Price: Free -
9
ScaleCloud
ScaleMatrix
Data-intensive AI, IoT and HPC workloads requiring multiple parallel processes have always run best on expensive high-end processors or accelerators, such as Graphic Processing Units (GPU). Moreover, when running compute-intensive workloads on cloud-based solutions, businesses and research organizations have had to accept tradeoffs, many of which were problematic. For example, the age of processors and other hardware in cloud environments is often incompatible with the latest applications or high energy expenditure levels that cause concerns related to environmental values. In other cases, certain aspects of cloud solutions have simply been frustrating to deal with. This has limited flexibility for customized cloud environments to support business needs or trouble finding right-size billing models or support. -
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Deliver enterprise-class management for running compute and data-intensive distributed applications on a scalable, shared grid. IBM Spectrum Symphony® software delivers powerful enterprise-class management for running compute-intensive and data-intensive distributed applications on a scalable, shared grid. It accelerates dozens of parallel applications for faster results and better utilization of all available resources. With IBM Spectrum Symphony, you can improve IT performance, reduce infrastructure costs and expenses and quickly meet business demands. Get faster throughput and performance for compute-intensive and data-intensive analytics applications to accelerate time-to-results. Achieve higher levels of resource utilization by controlling and optimizing the massive compute power available in your technical computing systems. Reduce infrastructure, application development, deployment and management costs by gaining control of large-scale jobs.
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11
Wolfram Language
Wolfram Language
We comply with providing the computational paradigm. The Wolfram Language provides access to computing power at a significantly higher level than ever before, leveraging built-in computational intelligence based on a wide variety of algorithms and real-world knowledge, carefully integrated over three decades. The Wolfram Language is scalable for programs both small and large, with out-of-the-box deployment both on-premises and in the cloud. In addition, the Wolfram Language builds on clear principles and an elegant unified symbolic framework to create what is now emerging as the world's most productive programming language, and the first true computational communication language for humans and AI.Starting Price: Free -
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Slurm
IBM
Slurm Workload Manager, formerly known as Simple Linux Utility for Resource Management (SLURM), is a free, open-source job scheduler and cluster management system for Linux and Unix-like kernels. It's designed to manage compute jobs on high performance computing (HPC) clusters and high throughput computing (HTC) environments, and is used by many of the world's supercomputers and computer clusters.Starting Price: Free -
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MATLAB
The MathWorks
MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design. -
14
MPI for Python (mpi4py)
MPI for Python
Over the last years, high performance computing has become an affordable resource to many more researchers in the scientific community than ever before. The conjunction of quality open source software and commodity hardware strongly influenced the now widespread popularity of Beowulf class clusters and cluster of workstations. Among many parallel computational models, message-passing has proven to be an effective one. This paradigm is specially suited for (but not limited to) distributed memory architectures and is used in today’s most demanding scientific and engineering application related to modeling, simulation, design, and signal processing. However, portable message-passing parallel programming used to be a nightmare in the past because of the many incompatible options developers were faced to. Fortunately, this situation definitely changed after the MPI Forum released its standard specification.Starting Price: Free -
15
Erlang
Erlang
Erlang is a programming language used to build massively scalable soft real-time systems with requirements on high availability. Some of its uses are in telecoms, banking, e-commerce, computer telephony and instant messaging. Erlang's runtime system has built-in support for concurrency, distribution and fault tolerance. OTP is set of Erlang libraries and design principles providing middle-ware to develop these systems. It includes its own distributed database, applications to interface towards other languages, debugging and release handling tools.Starting Price: Free -
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Coreshub
Coreshub
Coreshub provides GPU cloud services, AI training clusters, parallel file storage, and image repositories, delivering secure, reliable, and high-performance cloud-based AI training and inference environments. The platform offers a range of solutions, including computing power market, model inference, and various industry-specific applications. Coreshub's core team comprises experts from Tsinghua University, leading AI companies, IBM, renowned venture capital firms, and major internet corporations, bringing extensive AI technical expertise and ecosystem resources. The platform emphasizes an independent and open cooperative ecosystem, actively collaborating with AI model suppliers and hardware manufacturers. Coreshub's AI computing platform enables unified scheduling and intelligent management of diverse heterogeneous computing power, meeting AI computing operation, maintenance, and management needs in a one-stop manner.Starting Price: $0.24 per hour -
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BLooP
BLooP
Welcome to the Dictionary of Programming Languages, a compendium of computer coding methods assembled to provide information and aid your appreciation for computer science history. BLooP was a very simple recursive block structured language invented by Douglas Hofstadter for his book Godel, Escher, Bach. It features simple subroutine structure, very simple number and boolean handling, and recursion. The interesting aspect of BLooP was that it offered only bounded loop constructs, and was therefore incapable of expressing certain general recursive computations.Starting Price: Free -
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Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.
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19
Azure HPC
Microsoft
Azure high-performance computing (HPC). Power breakthrough innovations, solve complex problems, and optimize your compute-intensive workloads. Build and run your most demanding workloads in the cloud with a full stack solution purpose-built for HPC. Deliver supercomputing power, interoperability, and near-infinite scalability for compute-intensive workloads with Azure Virtual Machines. Empower decision-making and deliver next-generation AI with industry-leading Azure AI and analytics services. Help secure your data and applications and streamline compliance with multilayered, built-in security and confidential computing. -
20
Prolog
Prolog
Prolog is a logic programming language associated with artificial intelligence and computational linguistics. Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is intended primarily as a declarative programming language, the program logic is expressed in terms of relations, represented as facts and rules. A computation is initiated by running a query over these relations. Prolog was one of the first logic programming languages and remains the most popular such language today, with several free and commercial implementations available. The language has been used for theorem proving, expert systems, term rewriting, type systems, and automated planning, as well as its original intended field of use, natural language processing. Modern Prolog environments support the creation of graphical user interfaces, as well as administrative and networked applications. -
21
Torch
Torch
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner. -
22
NVIDIA TensorRT
NVIDIA
NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.Starting Price: Free -
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Tenstorrent DevCloud
Tenstorrent
We developed Tenstorrent DevCloud to give people the opportunity to try their models on our servers without purchasing our hardware. We are building Tenstorrent AI in the cloud so programmers can try our AI solutions. The first log-in is free, after that, you get connected with our team who can help better assess your needs. Tenstorrent is a team of competent and motivated people that came together to build the best computing platform for AI and software 2.0. Tenstorrent is a next-generation computing company with the mission of addressing the rapidly growing computing demands for software 2.0. Headquartered in Toronto, Canada, Tenstorrent brings together experts in the field of computer architecture, basic design, advanced systems, and neural network compilers. ur processors are optimized for neural network inference and training. They can also execute other types of parallel computation. Tenstorrent processors comprise a grid of cores known as Tensix cores. -
24
OpenVINO
Intel
The Intel® Distribution of OpenVINO™ toolkit is an open-source AI development toolkit that accelerates inference across Intel hardware platforms. Designed to streamline AI workflows, it allows developers to deploy optimized deep learning models for computer vision, generative AI, and large language models (LLMs). With built-in tools for model optimization, the platform ensures high throughput and lower latency, reducing model footprint without compromising accuracy. OpenVINO™ is perfect for developers looking to deploy AI across a range of environments, from edge devices to cloud servers, ensuring scalability and performance across Intel architectures.Starting Price: Free -
25
XRCLOUD
XRCLOUD
GPU cloud computing is a GPU-based computing service with real-time, high-speed parallel computing and floating-point computing capacity. It is ideal for various scenarios such as 3D graphics applications, video decoding, deep learning, and scientific computing. GPU instances can be managed just like a standard ECS with speed and ease, which effectively relieves computing pressures. RTX6000 GPU contains thousands of computing units and shows substantial advantages in parallel computing. For optimized deep learning, massive computing can be completed in a short time. GPU Direct seamlessly supports the transmission of big data among networks. Built-in acceleration framework, it can focus on the core tasks by quick deployment and fast instance distribution. We offer optimal cloud performance at a transparent price. The price of our cloud solution is open and cost-effective. You may choose to charge on-demand, and you can also get more discounts by subscribing to resources.Starting Price: $4.13 per month -
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Cerebras
Cerebras
We’ve built the fastest AI accelerator, based on the largest processor in the industry, and made it easy to use. With Cerebras, blazing fast training, ultra low latency inference, and record-breaking time-to-solution enable you to achieve your most ambitious AI goals. How ambitious? We make it not just possible, but easy to continuously train language models with billions or even trillions of parameters – with near-perfect scaling from a single CS-2 system to massive Cerebras Wafer-Scale Clusters such as Andromeda, one of the largest AI supercomputers ever built. -
27
Silq
Silq
Silq is a new high-level programming language for quantum computing with a strong static type system, developed at ETH Zürich. Silq was originally published at PLDI'20. -
28
Tencent Cloud GPU Service
Tencent
Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads. Improve your business efficiency and competitiveness with high-performance parallel computing capabilities. Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images. Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud.Starting Price: $0.204/hour -
29
LMCache
LMCache
LMCache is an open source Knowledge Delivery Network (KDN) designed as a caching layer for large language model serving that accelerates inference by reusing KV (key-value) caches across repeated or overlapping computations. It enables fast prompt caching, allowing LLMs to “prefill” recurring text only once and then reuse those stored KV caches, even in non-prefix positions, across multiple serving instances. This approach reduces time to first token, saves GPU cycles, and increases throughput in scenarios such as multi-round question answering or retrieval augmented generation. LMCache supports KV cache offloading (moving cache from GPU to CPU or disk), cache sharing across instances, and disaggregated prefill, which separates the prefill and decoding phases for resource efficiency. It is compatible with inference engines like vLLM and TGI and supports compressed storage, blending techniques to merge caches, and multiple backend storage options.Starting Price: Free -
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Bright Cluster Manager
NVIDIA
NVIDIA Bright Cluster Manager offers fast deployment and end-to-end management for heterogeneous high-performance computing (HPC) and AI server clusters at the edge, in the data center, and in multi/hybrid-cloud environments. It automates provisioning and administration for clusters ranging in size from a couple of nodes to hundreds of thousands, supports CPU-based and NVIDIA GPU-accelerated systems, and enables orchestration with Kubernetes. Heterogeneous high-performance Linux clusters can be quickly built and managed with NVIDIA Bright Cluster Manager, supporting HPC, machine learning, and analytics applications that span from core to edge to cloud. NVIDIA Bright Cluster Manager is ideal for heterogeneous environments, supporting Arm® and x86-based CPU nodes, and is fully optimized for accelerated computing with NVIDIA GPUs and NVIDIA DGX™ systems. -
31
APL
APL
APL is an array-oriented programming language that will change the way you think about problems and data. With a powerful, concise syntax, it lets you develop shorter programs that enable you to think more about the problem you're trying to solve than how to express it to a computer.Starting Price: Free -
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Xilinx
Xilinx
The Xilinx’s AI development platform for AI inference on Xilinx hardware platforms consists of optimized IP, tools, libraries, models, and example designs. It is designed with high efficiency and ease-of-use in mind, unleashing the full potential of AI acceleration on Xilinx FPGA and ACAP. Supports mainstream frameworks and the latest models capable of diverse deep learning tasks. Provides a comprehensive set of pre-optimized models that are ready to deploy on Xilinx devices. You can find the closest model and start re-training for your applications! Provides a powerful open source quantizer that supports pruned and unpruned model quantization, calibration, and fine tuning. The AI profiler provides layer by layer analysis to help with bottlenecks. The AI library offers open source high-level C++ and Python APIs for maximum portability from edge to cloud. Efficient and scalable IP cores can be customized to meet your needs of many different applications. -
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RAGFlow
RAGFlow
RAGFlow is an open source Retrieval-Augmented Generation (RAG) engine that enhances information retrieval by combining Large Language Models (LLMs) with deep document understanding. It offers a streamlined RAG workflow suitable for businesses of any scale, providing truthful question-answering capabilities backed by well-founded citations from various complex formatted data. Key features include template-based chunking, compatibility with heterogeneous data sources, and automated RAG orchestration.Starting Price: Free -
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Intel Open Edge Platform
Intel
The Intel Open Edge Platform simplifies the development, deployment, and scaling of AI and edge computing solutions on standard hardware with cloud-like efficiency. It provides a curated set of components and workflows that accelerate AI model creation, optimization, and application development. From vision models to generative AI and large language models (LLM), the platform offers tools to streamline model training and inference. By integrating Intel’s OpenVINO toolkit, it ensures enhanced performance on Intel CPUs, GPUs, and VPUs, allowing organizations to bring AI applications to the edge with ease. -
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TotalView
Perforce
TotalView debugging software provides the specialized tools you need to quickly debug, analyze, and scale high-performance computing (HPC) applications. This includes highly dynamic, parallel, and multicore applications that run on diverse hardware — from desktops to supercomputers. Improve HPC development efficiency, code quality, and time-to-market with TotalView’s powerful tools for faster fault isolation, improved memory optimization, and dynamic visualization. Simultaneously debug thousands of threads and processes. Purpose-built for multicore and parallel computing, TotalView delivers a set of tools providing unprecedented control over processes and thread execution, along with deep visibility into program states and data. -
36
AGVortex
AGVortex
AGVortex is the CAE program for mathematical modelling of fluid and gas flows around airfoils. Here is implemented innovational solver based upon vorticity dynamics. This approach allows to resolve LES turbulence model on the multi-core processors and clusters that use parallel computing. But it needs much less computing power. Fewer number of equations and unknown functions in flow dynamics gives a gain in calculation process and imposes lower requirements for the computational resources. So, technologically, 3D modelling using LES turbulence model is possible today. An application consists of 3D editor, control panel, modeling area. The planned improvements: new solid types, turbulence models based upon vorticity . The trial version has limitations on the size of the grid, maximum Reynolds number, restrictions in the settings. System requirements: Win x64, vc++ redistributable, openGL drivers.Starting Price: free -
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NVIDIA DRIVE
NVIDIA
Software is what turns a vehicle into an intelligent machine. The NVIDIA DRIVE™ Software stack is open, empowering developers to efficiently build and deploy a variety of state-of-the-art AV applications, including perception, localization and mapping, planning and control, driver monitoring, and natural language processing. The foundation of the DRIVE Software stack, DRIVE OS is the first safe operating system for accelerated computing. It includes NvMedia for sensor input processing, NVIDIA CUDA® libraries for efficient parallel computing implementations, NVIDIA TensorRT™ for real-time AI inference, and other developer tools and modules to access hardware engines. The NVIDIA DriveWorks® SDK provides middleware functions on top of DRIVE OS that are fundamental to autonomous vehicle development. These consist of the sensor abstraction layer (SAL) and sensor plugins, data recorder, vehicle I/O support, and a deep neural network (DNN) framework. -
38
PanGu-Σ
Huawei
Significant advancements in the field of natural language processing, understanding, and generation have been achieved through the expansion of large language models. This study introduces a system which utilizes Ascend 910 AI processors and the MindSpore framework to train a language model with over a trillion parameters, specifically 1.085T, named PanGu-{\Sigma}. This model, which builds upon the foundation laid by PanGu-{\alpha}, takes the traditionally dense Transformer model and transforms it into a sparse one using a concept known as Random Routed Experts (RRE). The model was efficiently trained on a dataset of 329 billion tokens using a technique called Expert Computation and Storage Separation (ECSS), leading to a 6.3-fold increase in training throughput via heterogeneous computing. Experimentation indicates that PanGu-{\Sigma} sets a new standard in zero-shot learning for various downstream Chinese NLP tasks. -
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IRIS
Global Market Solutions
IRIS workflow handles the global challenge of active counterparty credit risk management, from trading data acquisition to trade re-booking including curve stripping, consistent pricing, exhaustive aggregation module, hedge requirement computation and What-if scenarios. IRIS is a parallel distributed application permitting efficient utilization of multi-core systems. An HPC solution based on GPU and Multicore processors is also available to accelerate pricing and Greeks computation. The ability to plug IRIS engines into existing complex systems is a major design goal. The choice of .NET development framework ensures interoperability and integration with other languages. IRIS fully supports FpML and market data providers including Reuters, Bloomberg, Markit which ensures smooth data stream integration. IRIS internal data are fully accessible making computation details auditable. -
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OpenGL
OpenGL
OpenGL (Open Graphics Library) is a cross-language, cross-platform application programming interface for rendering 2D and 3D vector graphics. The API is typically used to interact with a graphics processing unit, to achieve hardware-accelerated rendering. Silicon Graphics, Inc. (SGI) began developing OpenGL in 1991 and released it on June 30, 1992. It is used for a variety of applications, including computer-aided design (CAD), video games, scientific visualization, virtual reality, and flight simulation. The OpenGL Registry contains specifications of the core API and shading language; specifications of Khronos- and vendor-approved OpenGL extensions; header files corresponding to the specifications; and related documentation including specifications, extensions, and headers for the GLX, WGL, and GLU APIs. -
41
Character.AI
Character.AI
Character.AI is bringing to life the science-fiction dream of open-ended conversations and collaborations with computers. We are building the next generation of dialog agents; with a long-tail of applications spanning entertainment, education, general question-answering and others. Our dialog agents are powered by our own proprietary technology based on large language models, built and trained from the ground up with conversation in mind. The Character.AI beta is based on neural language models. A supercomputer reads huge amounts of text and learns to hallucinate what words might come next in any given situation. Models like these have many uses including auto-complete and machine translation. At Character.AI, you collaborate with the computer to write a dialog - you write one character's lines, and the computer creates the other character's lines, giving you the illusion that you are talking with the other character. -
42
Visual Basic
Microsoft
Visual Basic is an object-oriented programming language developed by Microsoft. Using Visual Basic makes it fast and easy to create type-safe .NET apps. Visual Basic focuses on supplying more of the features of the Visual Basic Runtime (microsoft.visualbasic.dll) to .NET Core and is the first version of Visual Basic focused on .NET Core. Many portions of the Visual Basic Runtime depend on WinForms and these will be added in a later version of Visual Basic. .NET is a free, open-source development platform for building many kinds of apps. With .NET, your code and project files look and feel the same no matter which type of app you're building. You have access to the same runtime, API, and language capabilities with each app. A Visual Basic program is built up from standard building blocks. A solution comprises one or more projects. A project in turn can contain one or more assemblies. Each assembly is compiled from one or more source files.Starting Price: Free -
43
R
The R Foundation
R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.Starting Price: Free -
44
Arm MAP
Arm
No need to change your code or the way you build it. Profiling for applications running on more than one server and multiple processes. Clear views of bottlenecks in I/O, in computing, in a thread, or in multi-process activity. Deep insight into actual processor instruction types that affect your performance. View memory usage over time to discover high watermarks and changes across the complete memory footprint. Arm MAP is a unique scalable low-overhead profiler, available standalone or as part of the Arm Forge debug and profile suite. It helps server and HPC code developers to accelerate their software by revealing the causes of slow performance. It is used from multicore Linux workstations through to supercomputers. You can profile realistic test cases that you care most about with typically under 5% runtime overhead. The interactive user interface is clear and intuitive, designed for developers and computational scientists. -
45
Small Basic
Small Basic
Small Basic is the only programming language created especially to help students transition from block-based coding to text-based coding. By teaching the fundamental elements of syntax-based languages in an approachable manner, Small Basic gives students the skills and confidence to tackle more complex programming languages such as Java and C#. You can also build applications for Kinect, Lego Mindstorm, Raspberry Pi, Arduino, Oculus Rift, and more using Small Basic. Small Basic combines a friendly environment with a very simple language and a rich and engaging set of libraries to make your programs and games pop! In a matter of a few lines of code, you will be well on your way to creating your very own game! Share your programs with your friends and let them import your published programs and run them on their computers. Using the Silverlight player, you can even post your games on your own blogs and websites and play them in the browser.Starting Price: Free -
46
Pascal
Pascal
Pascal is a procedural and imperative programming language. Pascal is a simple and efficient programming language designed for developers that want to build applications in structured ways. Free Pascal is a mature, versatile, open source Pascal compiler. It can target many processor architectures: Intel x86 (16 and 32 bit), AMD64/x86-64, PowerPC, PowerPC64, SPARC, SPARC64, ARM, AArch64, MIPS, Motorola 68k, AVR, and the JVM. Supported operating systems include Windows (16/32/64 bit, CE, and native NT), Linux, Mac OS X/iOS/iPhoneSimulator/Darwin, FreeBSD and other BSD flavors, DOS (16 bit, or 32 bit DPMI), OS/2, AIX, Android, Haiku, Nintendo GBA/DS/Wii, AmigaOS, MorphOS, AROS, Atari TOS, and various embedded platforms. Additionally, support for RISC-V (32/64), Xtensa, and Z80 architectures, and for the LLVM compiler infrastructure is available in the development version. Additionally, the Free Pascal team maintains a transpiler for pascal to Javascript called pas2js. -
47
Substrate
Substrate
Substrate is the platform for agentic AI. Elegant abstractions and high-performance components, optimized models, vector database, code interpreter, and model router. Substrate is the only compute engine designed to run multi-step AI workloads. Describe your task by connecting components and let Substrate run it as fast as possible. We analyze your workload as a directed acyclic graph and optimize the graph, for example, merging nodes that can be run in a batch. The Substrate inference engine automatically schedules your workflow graph with optimized parallelism, reducing the complexity of chaining multiple inference APIs. No more async programming, just connect nodes and let Substrate parallelize your workload. Our infrastructure guarantees your entire workload runs in the same cluster, often on the same machine. You won’t spend fractions of a second per task on unnecessary data roundtrips and cross-region HTTP transport.Starting Price: $30 per month -
48
Java
Oracle
The Java™ Programming Language is a general-purpose, concurrent, strongly typed, class-based object-oriented language. It is normally compiled to the bytecode instruction set and binary format defined in the Java Virtual Machine Specification. In the Java programming language, all source code is first written in plain text files ending with the .java extension. Those source files are then compiled into .class files by the javac compiler. A .class file does not contain code that is native to your processor; it instead contains bytecodes — the machine language of the Java Virtual Machine1 (Java VM). The java launcher tool then runs your application with an instance of the Java Virtual Machine.Starting Price: Free -
49
Graphcore
Graphcore
Build, train and deploy your models in the cloud, using the latest IPU AI systems and the frameworks you love, with our cloud partners. Allowing you to save on compute costs and seamlessly scale to massive IPU compute when you need it. Get started with IPUs today with on-demand pricing and free tier offerings with our cloud partners. We believe our Intelligence Processing Unit (IPU) technology will become the worldwide standard for machine intelligence compute. The Graphcore IPU is going to be transformative across all industries and sectors with a real potential for positive societal impact from drug discovery and disaster recovery to decarbonization. The IPU is a completely new processor, specifically designed for AI compute. The IPU’s unique architecture lets AI researchers undertake entirely new types of work, not possible using current technologies, to drive the next advances in machine intelligence. -
50
Scheme
Scheme
Scheme is a general-purpose computer programming language. It is a high-level language, supporting operations on structured data such as strings, lists, and vectors, as well as operations on more traditional data such as numbers and characters. While Scheme is often identified with symbolic applications, its rich set of data types and flexible control structures make it a truly versatile language. Scheme has been employed to write text editors, optimize compilers, operating systems, graphics packages, expert systems, numerical applications, financial analysis packages, virtual reality systems, and practically every other type of application imaginable. Scheme is a fairly simple language to learn since it is based on a handful of syntactic forms and semantic concepts and since the interactive nature of most implementations encourages experimentation. Scheme is a challenging language to understand fully.Starting Price: Free
