Reconfigure.io: FPGA Cloud Development and Modern Alternatives

Reconfigure.io was a platform for developing FPGA-accelerated applications, with a software ecosystem centred on Go and cloud-based hardware development. If you arrived here looking for the original service, this page explains its technical focus, points to surviving project resources and outlines current development options.

This is an independent historical resource from StuartKerrs.com. It is not the original Reconfigure.io service, documentation portal or customer support channel.

Reconfigure.io at a glance

Reconfigure.io belongs in the history of programmable computing infrastructure. Its relevance is to developers exploring hardware acceleration, rather than businesses looking for a conventional website hosting account. The modern options below are documentation-based starting points, not a hands-on product ranking.

Question	Short answer
What was its focus?	FPGA development and hardware acceleration, with Go-based tools and examples.
Where can I find historical material?	The ReconfigureIO GitHub organisation and its public repositories.
What covers cloud FPGA infrastructure today?	Amazon EC2 F2 is one current option to investigate.
What covers higher-level FPGA design?	AMD Vitis HLS supports a C/C++-to-RTL workflow.
Is there a direct replacement?	The options cover different parts of development and deployment; do not assume compatibility with old projects.

What was Reconfigure.io?

The surviving ReconfigureIO GitHub organisation documents a Go-oriented FPGA ecosystem. It includes reco, a command-line client for the service, and sdaccel, a library for interacting with SDAccel from Go. Other repositories cover FPGA-oriented cryptography and binarised neural network acceleration.

The project's public examples repository includes addition, histogram, memory-copy and memory-access examples. These are useful historical reference points for understanding the kinds of computational operations developers were working with.

The important distinction is between writing software for a general-purpose processor and developing a hardware implementation for particular operations. Reconfigure.io's surviving tools sit within that second area. Their existence does not mean an arbitrary Go application can be moved unchanged onto an FPGA.

What happened to Reconfigure.io?

This page does not provide access to the former hosted platform. Public code remains available, but repository availability does not establish that the associated hosted service, accounts or support still operate. The surviving material cited here does not establish an authoritative closure date or a supported migration programme.

For an old project, treat those repositories as historical source material. Check dependencies, licences and service endpoints before attempting to rebuild it, and preserve a local copy of your own source code and build configuration.

Looking for the old documentation, tutorials or community?

Reconfigure.io's former web presence included separate documentation, Go API reference and community subdomains. Historical page records identify material covering FPGA-side Go support, setup, simulation, parallel histogram examples, addition tutorials and communication between application components.

Those records help identify a topic, but they do not reproduce the instructions or establish compatibility with current tools. This resource does not recreate the original API documentation or preserve individual forum conversations.

For example code: start with the public examples repository linked above. Match the example to the dependency versions recorded in your project before attempting to use it.

For old Go API references: identify whether you need host-side application interfaces or FPGA-side packages. Use the matching source revision where available. A similarly named function in another release is not evidence of identical behaviour.

For a missing tutorial or community answer: search for an archived copy of the exact original URL. If no copy survives, rebuild the investigation around the original technical question and a reproducible example. A modern product overview cannot substitute for an old troubleshooting answer.

Surviving source-code pointers: use the resources below to investigate an old project. They are historical references, not restored tutorials or a supported replacement service. Keep the original dependency revisions alongside your code.

What you were looking for	Useful surviving resource	What it does not establish
Parallel histogram or addition tutorials	The examples repository contains histogram-parallel and addition folders.	The code does not reproduce each historical tutorial or guarantee compatibility with current FPGA tools.
Command-line setup and tool usage	The reco command-line client provides source and historical usage information.	Its service-dependent commands do not establish that the former hosted endpoints remain available.
FPGA-side Go packages	The sdaccel library documents interaction with SDAccel from Go.	It is not a complete language-support specification for every historical compiler release.
Versioned Go API references, including v0.8.0	Identify the original package, host-side or FPGA-side role, and source revision through the ReconfigureIO repositories and your own project records.	A current repository branch cannot be assumed to match an old versioned API page.
Cryptography on FPGAs	The historical crypto library contains FPGA-oriented cryptography code.	It does not preserve the community discussion or establish suitability for present-day security requirements.
Neural-network acceleration examples	The brain repository contains a Go implementation and APIs for binarised neural-network acceleration on FPGAs.	Historical examples are not current performance benchmarks or a supported production platform.

Old style guides, release notes and troubleshooting pages: source revisions and commit history can help explain a particular version, but they do not replace the original documentation. Preserve the exact old URL when searching archives. Graph-optimisation tutorials and individual error messages need their original context; there is no supported reconstruction of those instructions on this page.

Old dashboard, sign-up and status links: this page cannot restore accounts, issue service tokens, accept support requests or reproduce incident history. Links to the former app.reconfigure.io and status.reconfigure.io hosts now serve only as historical reference points.

How FPGA cloud development differs from web hosting

An FPGA, or field-programmable gate array, contains programmable logic that can be configured into a digital circuit. Instead of relying entirely on a CPU executing instructions, a developer can build a specialised processing pipeline for part of an application.

That flexibility comes with engineering work. Data movement, memory access, numerical precision and the surrounding application all affect whether acceleration is worthwhile. A fast kernel does not automatically produce a faster end-to-end service.

For example, a process that spends most of its time waiting for a database query will not necessarily benefit from accelerating a small calculation. First identify the bottleneck, then consider whether changing the hardware addresses it.

For publishing websites, running WordPress or serving ordinary web applications, start with the requirements covered in our hosting guides. Our explanation of what a web server does provides a useful foundation for separating website delivery from specialist compute acceleration.

Modern alternatives: choose the part of the workflow you need

A replacement decision should begin with what your project needs to preserve: access to programmable hardware, a higher-level design workflow, or simply the ability to run the application. These are different requirements.

Option	Relevant use	Main limitation
Amazon EC2 F2	Developing and deploying FPGA accelerators in the cloud.	Requires an FPGA-specific development and deployment workflow.
AMD Vitis HLS	Creating RTL from suitable C/C++ functions.	Design tooling, rather than a complete hosted application service.
Conventional CPU infrastructure	Running the application when custom hardware is unnecessary.	Does not reproduce FPGA logic or its specialised execution model.

Amazon EC2 F2: cloud FPGA infrastructure

Amazon EC2 F2 instances provide FPGA-based cloud infrastructure using AMD hardware. AWS documents an FPGA development kit and Developer AMI, with a workflow for building and registering Amazon FPGA Images for deployment.

This addresses the infrastructure side of the problem: access to programmable hardware without purchasing your own accelerator server. It does not preserve Reconfigure.io's service interface or guarantee that historical code will build unchanged.

Before committing, check current region availability, account quotas, supported tool versions and instance pricing. Budget for development time, storage and data transfer alongside runtime. Historical tutorials mentioning another instance generation should not be treated as current F2 instructions.

AMD Vitis HLS: higher-level FPGA design

AMD Vitis HLS synthesises C/C++ functions into RTL, the hardware description used in subsequent implementation steps. AMD documents integration with Vivado and Vitis, plus simulation and analysis tools.

Its relevance is the higher-level design approach. The language and toolchain differ from Reconfigure.io's Go ecosystem, so moving a project involves engineering work rather than changing a service URL.

AMD states that C synthesis and simulation require no licence, while compilation of the generated RTL requires a valid Vivado licence. Check the requirements for your target device and deployment flow before budgeting. Vitis HLS is a development tool; hardware access and production operation are separate considerations.

Conventional cloud infrastructure: when acceleration is unnecessary

If the real objective is to restore a working application, rebuilding its computational component for a CPU may be more practical than recreating its FPGA implementation. That depends on its performance requirements and how much of the original application survives.

Establish a correct CPU baseline before choosing specialised infrastructure. It gives you something measurable to compare against and a potential fallback. Operational work still matters; our server management guide covers the broader responsibilities of maintaining a server environment.

How to assess an old Reconfigure.io project

Start with recoverability. Gather source files, build scripts, dependency versions, test inputs and expected outputs. Separate application code from the hardware-specific component and from calls to the former service.

Define correctness before speed. Identify numerical tolerances, data formats and edge cases. A replacement that runs quickly but changes results is not a successful migration.

Measure the whole workflow. Compare data loading, transfers, processing and result retrieval using representative inputs. Include the time and cost of maintaining the implementation, rather than judging only the accelerated function.

Prototype one bounded operation. Choose a small component with clear inputs and outputs before attempting a full port. Confirm that the target hardware, compiler and runtime work together, then decide whether the result justifies further investment.

Final verdict: preserve the useful ideas, reassess the infrastructure

Reconfigure.io's surviving projects provide a reference for Go-oriented FPGA development. For present-day work, separate the need for cloud hardware from the need for design tools, and evaluate each against the application you actually have.

The practical starting point is a working, measurable baseline. Explore a current FPGA workflow when a specific workload and performance requirement justify it. If conventional infrastructure already meets the requirement, there may be no business case for rebuilding the hardware accelerator.

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