Documentation

Download the latest versions of Achronix application notes, datasheets, product briefs, user guides and white papers.

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Title Description Version Released Date Document File
Reduce Speech Transcription Costs by up to 90% with CAI (WP030)

Conversational artificial intelligence (CAI) uses deep learning (DL), a subset of machine learning (ML), to automate speech recognition, natural language processing and text to speech using machines. Achronix and Myrtle.ai are teaming up to deliver an ASR platform consisting of a 200W, x16 PCIe Gen4-based accelerator card and the associated software which together can sustain up to 4000 RTS concurrently, processing up to 1 million five-minute transcriptions per 24-hour period — reducing costs by as much as 90% versus cloud-based APIs.

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Achronix FPGAs Optimize AI in Industry 4.0 and 5.0 (WP027)

Industry has come a long way over in the last three hundred years. Machines were first introduced in the 1700s, mainly water and steam driven, introducing the Industrial Revolution in the late 1700s. Automation and computer technology would enter the picture in the late 1960's, paving the way for the eventual automation, artificial intelligence (AI) and networked solutions of today. Although it might appear that humans are no longer in the picture, Industry 5.0 is bringing us full circle by combining the precision and efficiency of robotic systems, driven largely by AI, with the ingenuity and real-time thought of the human mind — all leading to more optimal manufacturing environments.

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FPGAs and eFPGAs Accelerate ML Inference at the Edge (WP026)

With the rapid proliferation of Internet-of-Things (IoT) and billions of connected devices, there is a paradigm shift taking place where big data is not only being processed in the core data center but also at the network edge. Field Programmable Gate Arrays (FPGAs), sitting at the intersection of performance and flexibility, are a promising solution for deep learning edge inference applications.

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Data Orchestration Supports the Next Advance in AI (WP025)

Artificial intelligence (AI) and machine learning (ML) technologies now power a rapidly expanding range of product and applications from deeply embedded systems to hyperscale data-center deployments. Although there is a huge degree of diversity in the hardware designs supporting these applications, all require hardware acceleration. Data orchestration encompasses the pre- and post-processing operations that ensure the data seen by a machine learning engine arrives at an optimal speed and in the most suitable form for efficient processing.

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An FPGA-Based Solution for a Graph Neural Network Accelerator (WP024)

Thanks to the rise of big data and the rapid increase in computing power, machine learning technology has experienced revolutionary development in recent years. Machine learning tasks such as image classification, speech recognition, and natural language processing, operate on Euclidean data with a certain size, dimension, and an orderly arrangement. However, in many realistic scenarios, data is represented by complex non-Euclidean data such as graphs. In this context, many new graph-based machine learning algorithm, or graph neural networks (GNNs), are constantly emerging in academia and industry.

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Title Description Version Released Date Document File
Understanding ACE Timing Reports (AN024)

Accurate timing constraints and proper understanding of timing analysis reports are critical to successful FPGA design projects. This application note introduces ACE users to the structure of ACE timing reports generated during an ACE place-and-route run.

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Speedcore User Interface Timing Sign-off Methodology (AN009)

Timing sign-off between the host ASIC and the Speedcore boundary is one of the most crucial steps in ensuring proper integration of a Speedcore instance into a customer's SoC.

1.1 Speedcore_User_Interface_Timing_Sign-off_Methodology_AN009.pdf
SoC-Speedcore Interface Tests (AN022)

The input and output paths between the host SoC and a Speedcore instance are an important test component. It is essential to have a structure that ties seamlessly to the SoC's test flow without requiring special functions such as loading a bitstream in the Speedcore instance.

1.0 SoC-Speedcore_Interface_Tests_AN022.pdf
Migrating to Achronix eFPGA Technology (AN014)

Many users transitioning to Achronix eFPGA technology will be familiar with existing FPGA solutions from other vendors. Although Achronix technology and tools are similar to existing FPGA technology and tools, there are some differences. Understanding these differences are needed to achieve the very best performance and quality of results (QoR).

1.1 Migrating_to_Achronix_eFPGA_Technology_AN014.pdf
ACE ECO Flow Guide (AN015)

This tutorial serves as an introduce to the ACE engineering change order (ECO) suite — a set of Tcl commands that can add or remove instances, nets, pin connections, and more from a placed-and-routed design.

1.0 ACE_ECO_Flow_Guide_AN015.pdf
Title Description Version Released Date Document File
Speedcore eFPGA Product Brief (PB028)

Speedcore IP is embedded FPGA (eFPGA) that can be integrated into an ASIC or SoC. Customers specify their logic, RAM and DSP resource needs, then Achronix configures the Speedcore IP to meet their individual requirements.

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Maximize Hardware Assurance Using Embedded FPGAs (PB035)

Implementing a secure IP solution when developing a custom ASIC involves overcoming many risks along the development, manufacturing and supply chain flow. Hardware assurance continues to become more critical for military and defense applications as worldwide threats increase. By using an eFPGA IP solution to store mission critical IP, supply chain security is greatly simplified compared to the traditional ASIC design flow.

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Speedcore eFPGA Test Chip Evaluation Board (PB030)

The Speedcore eFPGA evaluation board from Achronix contains the 16-nm Speedcore eFPGA test chip. The evaluation board’s Speedcore test chip has been customized with the right blend of resources such as LUTs, BRAMs, DSP64s, DFFs and a number of I/O so as to provide an optimum programmable platform for demonstrating, evaluating and testing Achronix’s Speedcore technology.

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Title Description Version Released Date Document File
Snapshot User Guide (UG016)

Snapshot is the real-time design debugging tool for Achronix FPGAs and cores. This guide details the setup and operation of the Snapshot feature using a simple reference design.

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Speedster7t 2D Network on Chip User Guide (UG089)

The Speedster7t FPGA family of devices has a network hierarchy that enables extremely high-speed dataflow between the FPGA core and the interfaces around the periphery, as well as between logic within the FPGA itself. This on-chip network hierarchy supports a cross-sectional bidirectional bandwidth of 20 Tbps. It supports a multitude of interface protocols including GDDR6, DDR4/5, 400G Ethernet, and PCI Express Gen5 data streams, while greatly simplifying access to memory and high-speed protocols. Achronix's two-dimensional network on chip (2D NoC) provides for read/write transactions throughout the device, as well as specialized support for 400G Ethernet streams in selected columns. The features of the 2D NoC described in this user guide generally pertain to the entire Speedster7t family of devices. In order to help users understand specific connections and features of the 2D NoC, this user guide focuses on the 2D NoC as implemented in the AC7t1500 device.

1.2 Download
ACE Installation and Licensing Guide (UG002)

This guide covers software installation and licensing of ACE software under both Windows and Linux operating software.

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Speedster7t GDDR6 User Guide (UG091)

The Speedster7t FPGA family provides multiple GDDR6 subsystems enabling full utilization of the high-bandwidth efficiency of these interfaces for critical applications. This guide provides the details for implementing the GDDR6 IP in custom designs.

2.0 Download
Speedster7t Ethernet User Guide (UG097)

Speedster7t devices include high-speed Ethernet interfaces, which can support a wide variety of Ethernet packet protocols and speeds of up to 400 Gbps per channel. These Ethernet interfaces are paired with latest generation SerDes which individually support 100 Gbps data rates. With eight of these SerDes per Ethernet interface, each interface can support 2× 400 Gbps Ethernet IP channels.

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