Recent Content
How to Generate Altera HAL for HPS?
Hi, I am using Quartus 26.1 with the Agilex 5 Modular Development Kit (Device number: A5ED065BB32AE6SR0) and I have a few questions about BSP Generation for Hard Processor System (HPS). For reference I am following the Quartus Prime Pro Edition Version 26.1 User Guide. 1. How do I generate Altera HAL for HPS? When I use the BSP Editor in platform designer, I can only generate the system.h file that only has macros for EMIF, even though other peripherals are also connected to the HPS. How do I generate macros for the H2F bridges and HAL API Files for the HPS? 2. How do I input a SOPCINFO file into the BSP Editor? The Quartus Prime Pro Edition User Guide shows that I should be able to input SOPCINFO file as the system file (see above image) but Quartus only gives me the options of QSYS and IP file (see below image). Thank you for the help!SolvedQuartus crashes on long carry chain in Agilex 5 FPGAs
We try to manually place a carry chain in the Agilex 5 FPGAs which consists of more than 40 LABs. When we place this carry chain using set_location_assignment, Quartus crashes during the placement phase whenever the carry chain is longer than 40 LABs. Is it expected that the carry chain cannot be made longer than 40 LABs in the Agilex 5 FPGAs? Crash was observed on Quartus 25.3 and Quartus 26.1 for the devices A5ED065BB32AE4S and A5ED013BB32AE4SCS. Internal Error: Sub-system: FLABS, File: /quartus/fitter/flabs/flabs_util.cpp, Line: 96 p_to_fill->next == FLABS_OPEN143Views0likes4CommentsAgilex-5 supported Transceivers
I am currently evaluating the capabilities of the Altera Dev Board DK-A5E065AB32AEA. As most SFP+ and QSFP+ Transceivers are often vendor-locked, is there a list of qualified Transceivers available? Intel E10GSFPSR and another Xcvr marketed as support for Nvidia did not work in my case, as I attempted to do the initial Testing using BTS App as per document D554638 Which transceivers were used by Intel(Altera) for qualifiying/testing the development board DK-A5E065AB32AEA ?693Views0likes7CommentsAgilex3 ip fragmented packets gets corrupted
Hi I have a problem where the agilex3 HPS is not able to correctly reassemble ip-fragmented packets, I have included two pcaps one that show what the host is sending to the agilex and one that show the reception on the agilex. As you can see in the agilex.pcapng some of the packets gets corrupted in strange ways and gets wrong checksum. I use the DK-A3W135BM16AEA: Agilex® 3 FPGA and SoC C-Series Development Kit and has based my project on this example: https://altera-fpga.github.io/rel-25.3.1/embedded-designs/agilex-3/c-series/gsrd/ug-gsrd-agx3/ Anybody know whats going on here?234Views0likes5CommentsLooking for example testbench for Cyclone-V Transceiver Custom_PHY IP from UG-01080-1.7
Hi, I am looking into the Altera Transceiver PHY IP Core User Guide, UG-01080-1.7 (June 2012). I followed section 7, “Custom PHY IP Core” to generate a custom PHY core using the Quartus 23.1-based MegaWizard and IP Catalog for my Cyclone-V FPGA. I have all Verilog files generated for the custom PHY IP in a new folder tst_xcvr_phy_custom. Next, I tried to do a basic loopback simulation of this custom PHY core. Page 7-28 in the user guide states : ............ However when I try the "Altera wiki" link I get .... not sure why I get this, I do have an active Altera account. Perhaps this Altera-Wiki has been migrated to a Github Altera Transceivers (PHY IP) examples repo ? Can someone help me get an example testbench for the Cyclone-V custom PHY IP ? I have QuestaSim and ModelSim for simulating with it.98Views0likes5CommentsQuestions About Custom Linux Device Tree Handling in the Agilex 5 GSRD kas Build Environment
Hello, I have two questions regarding the following kas build environment: https://github.com/altera-fpga/agilex5e-ed-gsrd/tree/main/dk-a5e065bb32aea-enablement/baseline-a55/software/yocto_linux Custom Device Tree Application in FPGA Configuration First Mode My understanding is that FPGA_ENABLE_CORE_PGM, defined in kas.yml, is used to enable or disable FPGA core configuration from HPS, effectively selecting between HPS Boot First and FPGA Configuration First modes. However, when FPGA_ENABLE_CORE_PGM is set to 0 (FPGA Configuration First), I observed that the custom Linux Device Tree specified by CUSTOM_LINUX_DTS_FILE in machine.yml is not applied. After investigating the build flow, it appears that the kernel recipe (linux-socfpga-lts_%.bbappend) checks the value of FPGA_CORE_PGM_ENABLE (which corresponds to FPGA_ENABLE_CORE_PGM) to determine whether a custom Linux Device Tree should be applied. On the other hand, kas.yml also defines CUSTOM_LINUX_DEVICE_TREE, which seems to be the variable specifically intended to control custom Linux Device Tree usage. Therefore, I would have expected the kernel recipe to check CUSTOM_LINUX_DT (which corresponds to CUSTOM_LINUX_DEVICE_TREE) rather than FPGA_CORE_PGM_ENABLE. As an experiment, I made the following changes: 1) Modified the conditional check in the kernel recipe Before: FPGA_CORE_PGM_ENABLE After: CUSTOM_LINUX_DT 2) Set the following in kas.yml CUSTOM_LINUX_DEVICE_TREE = "1" With these changes, the custom Linux Device Tree was successfully applied even when using FPGA Configuration First mode. Could you please confirm whether the current implementation is intentional? If this behavior is by design, could you also explain the reason for using FPGA_CORE_PGM_ENABLE to determine whether a custom Linux Device Tree should be applied? Definition Location of CUSTOM_LINUX_DTS_FILE While reviewing the README located under: meta-custom/recipes-kernel/linux/device-tree/ I found the following statement: "FIT image - kernel.itb will use the custom device tree in CUSTOM_LINUX_DTS_FILE if defined in kas/bsp.yml, else it will use Linux Kernel in-tree device tree defined using LINUX_DTS_FILE in kas/bsp.yml." However, I observed that defining CUSTOM_LINUX_DTS_FILE in kas/bsp.yml does not seem to have any effect. After further investigation, I noticed that CUSTOM_LINUX_DTS_FILE is already defined by default in kas/machine.yml, and it appears that the value from machine.yml is actually being used. In addition, LINUX_DTS_FILE is also defined by default in kas/machine.yml. Based on these observations, I am wondering whether the README might contain a typo, and that the references to kas/bsp.yml should actually be kas/machine.yml. Could you please confirm whether this understanding is correct? Thank you for your time and support.Solved180Views0likes3CommentsAgilex™ 7 I-Series FPGA Transceiver SoC Development Kit GSRD Build
I am attempting to build the GSRD using the Intel® Agilex™ 7 I-Series FPGA Transceiver SoC Development Kit (4x F-Tile) DK-SI-AGI027FA. Quartus Version: 24.3.1 Reference Document: https://altera-fpga.github.io/rel-24.3.1/embedded-designs/agilex-7/i-series/soc/gsrd/ug-gsrd-agx7i-soc/ When running the "Build Hardware Design" procedure according to the instructions: make BOARD_TYPE=devkit_fm87 BOARD_PWRMGT=linear QUARTUS_DEVICE=AGIB027R31B1E1V ENABLE_HPS_EMIF_ECC=1 FPGA_SGPIO_EN=1 HPS_F2S_IRQ_EN=1 generate_from_tcl all It throws the following log error and fails to proceed: make[1]: *** [Makefile:817: qsys_generate_qsys] Error 1 make[1]: Leaving directory '/home/nict/p.agilex7_gsrd/gsrd.dk_si_agi027fa/agilex_soc_devkit_ghrd' make: *** [Makefile:833: generate_from_tcl] Error 2 Could you please advise what might be causing this issue, or let me know which logs (such as QSYS/Platform Designer logs) I should check?44Views0likes1CommentUnstable fpga programming using HPS(Agilex3)
Hi I have a problem where the fpga programming sometime fail when using the overlay method described here under "Reconfiguring Core Fabric from Linux": https://altera-fpga.github.io/rel-25.3.1/embedded-designs/agilex-3/c-series/boot-examples/ug-linux-boot-agx3/#reconfiguring-core-fabric-from-u-boot Here I have first two successful attempt then it fail on the third: root@agilex3:~# rmdir /sys/kernel/config/device-tree/overlays/0 ; sleep 1 ; mkdir /sys/kernel/config/device-tree/overlays/0 ; cd /lib/firmware/ ; sleep 1; echo overlay.dtb >/sys/kernel/config/device-tree/overlays/0/path rmdir: '/sys/kernel/config/device-tree/overlays/0': No such file or directory [ 182.671913] fpga_manager fpga0: writing overlay.rbf to Stratix10 SOC FPGA Manager [ 184.865664] OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-region/firmware-name [ 184.876007] OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-region/config-complete-timeout-us root@agilex3:/lib/firmware# rmdir /sys/kernel/config/device-tree/overlays/0 ; sleep 1 ; mkdir /sys/kernel/config/device-tree/overlays/0 ; cd /lib/firmware/ ; sleep 1; echo overlay.dtb >/sys/kernel/config/device-tree/overlays/0/path [ 196.530735] fpga_manager fpga0: writing overlay.rbf to Stratix10 SOC FPGA Manager [ 198.659279] OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-region/firmware-name [ 198.669650] OF: overlay: WARNING: memory leak will occur if overlay removed, property: /fpga-region/config-complete-timeout-us root@agilex3:/lib/firmware# rmdir /sys/kernel/config/device-tree/overlays/0 ; sleep 1 ; mkdir /sys/kernel/config/device-tree/overlays/0 ; cd /lib/firmware/ ; sleep 1; echo overlay.dtb >/sys/kernel/config/device-tree/overlays/0/path [ 214.383163] fpga_manager fpga0: writing overlay.rbf to Stratix10 SOC FPGA Manager [ 217.508857] arm-smmu-v3 16000000.iommu: CMD_SYNC timeout at 0x00004405 [hwprod 0x00004408, hwcons 0x00004405] [ 217.509907] arm-smmu-v3 16000000.iommu: CMD_SYNC timeout at 0x00004407 [hwprod 0x00004408, hwcons 0x00004405] U-Boot SPL 2025.10 (May 18 2026 - 08:34:29 +0000) Reset state: Cold MPU 800000 kHz L4 Main 400000 kHz L4 sys free 100000 kHz L4 MP 200000 kHz L4 SP 100000 kHz SDMMC 200000 kHz init_mem_cal: Initial DDR calibration IO96B_0 succeed DDR: Calibration success is_mailbox_spec_compatible: IOSSM mailbox version: 1 LPDDR4: 1792 MiB ecc_interrupt_status: ECC error number detected on IO96B_0: 0 SDRAM-ECC: Initialized success Does anybody know how to debug and fix this? I'm using Quartus Prime Version 25.3.0 Build 109 Devboard: DK-A3W135BM16AEA: Agilex™ 3 FPGA and SoC C-Series Development Kit327Views0likes12Comments
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Recent Blogs
As AI, cloud, and high-performance computing systems continue to scale, data center operators need more bandwidth within increasingly constrained power and thermal envelopes. Linear Pluggable Optics (LPO) offers an important path forward by simplifying optical modules, reducing power consumption, and lowering latency. LPO places signal-conditioning responsibilities in the host device, allowing the optical module to operate without the DSP used in traditional retimed optics. This architecture can reduce optical module power by 30% to 40%, helping data center designers increase connectivity density while simplifying cooling and thermal management. Altera Brings LPO to the FPGA Market Altera is the first FPGA provider to publicly demonstrate Linear Pluggable Optics interoperability using production FPGA devices. Continued validation with LPO modules from Amphenol and FS further demonstrates the breadth of the emerging ecosystem supported by Altera. Agilex® 7 FPGAs and SoCs bring the power and latency advantages of LPO to programmable platforms used in SmartNICs, data processing units, AI accelerators, and custom infrastructure. The initial public demonstration established that Agilex 7 devices could successfully interoperate with 400G LPO modules. The latest validation advances that milestone by confirming that the implementation meets the performance requirements expected for deployment in demanding data center environments. Validated for Real Deployment Conditions Comprehensive testing confirms that Agilex 7 F-Tile transceivers meet the electrical and link-performance requirements defined by the 100G-DR-LPO specification. The validation demonstrated: Compliance with the required transmit, receive, and link-performance criteria Successful interoperability with LPO modules from Amphenol and FS Successful LPO connectivity across distances from 1 meter to 500 meters Consistent performance across temperature and voltage conditions Measurable performance margin beyond required thresholds Testing covered demanding signal conditions, voltage variation, and temperatures ranging from minus 40 degrees Celsius to 105 degrees Celsius for electrical characterization. Functional link testing included a 1-meter LPO connection, a 100-meter active optical cable, and 500-meter LPO modules from Amphenol and FS. The results demonstrate robust, repeatable operation across multiple module suppliers and link distances, with measurable margin relative to the required performance limits. For customers, this validation provides confidence that Agilex® 7 support for LPO is ready for real-world deployment. Following the industry’s first public FPGA interoperability demonstration, the solution has now been evaluated against LPO performance requirements using modules from multiple suppliers and over link distances up to 500 meters. Together, these results demonstrate a practical foundation for deploying LPO connectivity in next-generation data center systems. More Efficient Connectivity for AI and Cloud Infrastructure The value of LPO grows as data centers deploy more high-speed optical connections. Eliminating the DSP from each optical module can reduce power across thousands of links, simplify optical module design, ease thermal pressure at the front panel, and support lower-latency data movement. Agilex 7 FPGAs add programmability to this more efficient optical architecture. Customers can combine LPO connectivity with packet processing, acceleration, security, telemetry, and evolving protocol support on a single adaptable platform. This flexibility is especially valuable for AI clusters and cloud infrastructure, where workloads, network architectures, and connectivity standards continue to evolve. Validation with multiple module vendors also gives system designers greater flexibility as the LPO supplier ecosystem continues to develop. Ready for the Next Generation of Data Centers The combination of public interoperability and comprehensive validation marks a major step for LPO in the FPGA market. Altera has demonstrated that LPO works with production Agilex 7 devices and validated that the solution meets key LPO requirements with measurable operating margin. This gives customers a proven foundation for evaluating and deploying lower-power, lower-latency optical connectivity in real data center environments. With Agilex® 7 FPGAs, LPO is ready for real-world data center deployment.
23 days ago0likes
Security requirements are entering a new phase. Systems being designed today may remain deployed for many years, while regulatory expectations, cryptographic standards, and threat models continue to evolve. For designs in industrial, communications, infrastructure, aerospace, defense, and embedded applications, long-term security is becoming a core platform requirement. FPGA-based designs allow designs to meet today’s security needs and evolve with tomorrow’s requirements. Altera is now offering Agilex® 3 and Agilex® 5 devices with PQC-enabled secure boot and configuration support, helping customers prepare for the next generation of security requirements. With the Quartus® Prime Pro Edition 26.1.1 release, customers can begin using a PQC flow that works with Agilex 3 and Agilex 5 based hardware. This milestone extends the security architecture already built into the Agilex platform. Agilex devices use the Secure Device Manager as a hardware root of trust for secure configuration and device management. By combining PQC-capable devices with Quartus software enablement, Altera is helping customers strengthen the FPGA chain of trust as post-quantum requirements move from planning to implementation. The value is immediate and practical. Customers can start designing with supported devices today, while using Quartus 26.1.1 to take advantage of the current software flow. This gives teams a path to address emerging compliance and security expectations without needing a future platform redesign. The same hardware foundation also allows for additional security enhancements over time. Customers designing with PQC-capable Agilex 3 and Agilex 5 devices can benefit from planned software and firmware improvements enabled by the underlying hardware, with no further FPGA hardware upgrade required for those enhancements. Agilex 3 devices bring this capability to power- and cost-optimized FPGA and SoC designs used in embedded, edge, industrial, control, and platform-management applications. Agilex 5 devices extend the same security direction into mid-range FPGA and SoC designs that require higher performance, greater integration, and broader system capability. Post-quantum readiness will continue to advance, and Altera is building that evolution into the Agilex platform roadmap. With PQC-capable Agilex 3 and Agilex 5 devices and Quartus 26.1.1 software enablement, customers have a practical starting point today and a scalable foundation for future security enhancements.
28 days ago0likes
Altera has started to sample Agilex® 5 D-Series FPGA devices to customers, expanding the Agilex 5 family for customers building higher-performance midrange systems. This adds a second Agilex 5 path alongside Agilex 5 E-Series FPGAs, which are already in full production. Agilex 5 E-Series remains the production-ready choice for power- optimized midrange designs. It is a strong fit when customers need production availability, efficient power, and right-sized capability for applications such as industrial control, edge compute, physical AI, and embedded systems. Agilex 5 D-Series extends the family for designs that need more system performance headroom. It is intended for applications that place heavier demands on signal processing, embedded memory, memory bandwidth, and fabric performance, including broadcast, wireless, video, AI-enabled embedded systems, and higher-performance applications that benefit from memory interfaces such as DDR5 and LPDDR5 capability. One Agilex 5 family, two design paths Agilex 5 E-Series Agilex 5 D-Series In full production Engineering samples available Power-optimized midrange designs Higher-performance midrange designs Right-sized logic and efficient power More DSP, embedded memory, EMIF bandwidth, and higher DDR and LPDDR bandwidth Industrial control, edge compute, physical AI and embedded systems Data Center, Communications, Broadcast, video, and AI-enabled embedded systems Together, Agilex 5 E-Series and D-Series enable customers a clearer way to choose the right midrange FPGA path: production deployment today with E-Series, or higher-performance design evaluation with D-Series. Customers evaluating Agilex 5 D-Series can begin real-silicon design work with Quartus® Prime Pro Edition 26.1.1 support. To order Agilex 5 D-Series engineering samples, please contact your Altera representative. Visit the Agilex 5 D-Series page Visit the Quartus Pro 26.1 Page
28 days ago0likes
Quartus® Prime Pro Edition 2026.1.1 expands memory options across the Agilex® FPGA portfolio. Memory is increasingly setting the performance, power, and lifecycle limits of modern systems. AI acceleration, packet processing, storage, video, industrial automation, and edge computing all depend on moving large amounts of data efficiently. At the same time, memory availability and vendor transitions can force design teams to revisit component choices long after a platform architecture has been selected. With Quartus® Prime Pro Edition 2026.1.1, Altera expands memory options across the Agilex portfolio. The release brings higher-speed DDR5 and LPDDR5 options to Agilex 7 M-Series FPGAs and SoCs, broadens component choice through documented LPDDR5X device support, and extends LPDDR5 support to Agilex 3 FPGAs and SoCs. Together, these enhancements give designers greater flexibility to balance performance, power, footprint, memory cost, and supply continuity. What is new with Quartus Prime Pro Edition 2026.1.1 Enhancement Customer value DDR5-6400 and LPDDR5-6400 on Agilex 7 M-Series devices Higher Memory Bandwidth Raises the maximum supported memory data rate from 5600 to 6400 MT/s, an increase of more than 14%. DDR5 delivers up to 204.8 GB/s of aggregate bandwidth, while LPDDR5 provides a lower-power, compact-footprint option for bandwidth-intensive designs. LPDDR5X device use in LPDDR5-compatible mode New Sourcing Option Adds sourcing flexibility when LPDDR5 availability, or component strategy favors an LPDDR5X device. LPDDR5 now available for Agilex 3 devices New Memory Support Added Brings a modern low-power memory option to power- and cost-optimized Agilex 3 device configurations. Two 6400 MT/s paths for high-performance systems Agilex 7 M-Series FPGAs and SoCs already combine high logic density, high-speed connectivity, and advanced external memory functionality in a device family available today in full-volume production. Quartus Prime Pro Edition 2026.1.1 strengthens that family’s offering with DDR5-6400 and LPDDR5-6400 in approved configurations. For DDR5, the move from 5600 MT/s to 6400 MT/s increases the maximum data rate by more than 14%. That additional throughput can help AI, networking, storage, and infrastructure designs sustain higher data movement without expanding the FPGA footprint. It can also give architects more flexibility in how they meet a target bandwidth, including the potential to optimize channel count, DIMM selection, board space, and subsystem complexity when the application and supported configuration allow it. LPDDR5-6400 brings a second option to the same top-line interface rate. LPDDR5 is increasingly relevant beyond mobile products because it combines strong bandwidth with lower I/O power and a compact board footprint. Those characteristics are valuable in embedded systems, smart network interface cards, industrial platforms, edge compute, and other designs, where thermal limits and board area matter alongside performance. The result is a high-end FPGA platform that lets designers choose between DDR5 for capacity and server-class memory options, or LPDDR5 for power and footprint efficiency, while reaching up to 6400 MT/s and 204.8 GB/s of aggregate memory bandwidth in selected Agilex 7 M-Series device configurations. LPDDR5X device compatibility adds practical supply-chain flexibility The LPDDR5X enhancement addresses a different customer need. LPDDR5X devices are backward compatible with the LPDDR5 interface, so components can be used with an Agilex LPDDR5 memory interface while operating at the same speeds, voltages, and specifications as the LPDDR5 configuration. Customers can now design with LPDDR5X components in LPDDR5-compatible mode with greater confidence, backed by documented Altera support process. A complete memory offering across the Agilex portfolio Because the Agilex portfolio spans high-performance, mid-range, and power- and cost-optimized devices, customers can carry a consistent FPGA architecture and Quartus development flow across products with very different memory requirements. That continuity helps reduce redesign effort and gives engineering teams more freedom to scale compute, connectivity, and memory together. Teams can preserve DDR4 or LPDDR4 where product requirements, temperature range, or supply conditions still favor those technologies. New designs can move to DDR5 or LPDDR5 for higher bandwidth and better system efficiency. LPDDR5X device compatibility provides an additional sourcing path without requiring customers to redesign a separate memory interface. Explore Agilex FPGA external memory solutions and review the Quartus Prime Pro Edition 2026.1.1 documentation for supported devices, speed grades, memory components, and configurations.
28 days ago0likes
A customer recently shared with me an interesting way they viewed the updated Altera brand: It’s like a long-time friend who had moved away for a few years but is now back and it’s time to get caught up. One of the things customers might want to 'catch up' on is Altera's efforts with regards to AI. It started when early FPGA products included the first basic digital signal processing (DSP) circuits within the FPGA fabric to improve performance for math-based logic, such as Fast Fourier transforms (FFTs) and finite impulse response (FIR) filters. These early enhancements improved general purpose FPGA-based computing but since 2015, our focus has shifted to improving AI capabilities in both silicon and software tools. DSP capabilities have gotten more sophisticated (fixed point, floating point, small and large bit precisions, etc.) and the quantity of available DSPs within a single device, have increased dramatically. Modern FPGAs are now capable of handling complex equations, especially those needed with the introduction of AI. This historical reminisce catches us up all the way until today’s news, where the latest Altera FPGA family is now broadly available to any customer who wants it; Agilex™ 5 SoC FPGAs, the first FPGAs infused with AI tensor blocks throughout the FPGA fabric. A short list of features that would be attractive to embedded or intelligent edge applications include: For those haven’t heard about Agilex™ 5 devices before today, here is how you can get started: Learn about the family. Review technical details. Download FPGA software. Free for anyone wanting access to Agilex™ 5 E-Series devices: Download Quartus® Prime Pro Test drive hardware (generally available now, lead-times may apply, via franchised distributors): Buy Altera development kits or 3rd party boards and SoMs The initial wave of board/SoM options include 9+ variants, with more coming. Evaluate AI or embedded options: Test out the FPGA AI Suite. Contact Altera sales for limited time introductory pricing. Utilize 3rd party tools (Arm DS, MathWorks) to design for the new, best-in-class Arm dual-A76 + dual-A55 based SoC subsystem or RISC-V based Nios® V soft IP processors. Altera is announcing the Agilex™ 5 family broad availability coincident with Embedded World 2024 because it is one of the key markets this mid-range FPGA family was architected for. Embedded customers clearly told us they perceive a lack of adequate compute in embedded processors, see a big need to fill security gaps, and want to add AI into their next generation systems. Agilex™ 5 devices can address all these concerns. Coming back to our initial topic, AI: GPUs are certainly a popular choice for AI training, but power consumption of GPUs for AI inferencing may be too high for intelligent edge or embedded applications. Instead of adding a separate GPU/AI semiconductor device to an embedded system (resulting in higher cost, more power, more thermal, etc.), why not add the AI function into an FPGA already planned to be used in embedded/edge equipment? For decades, FPGAs have been used in embedded/edge and communication systems for real-time control, IO connectivity, or image/data processing. The estimates on Agilex™ 5 device AI performance look good compared to equivalent class competitors. Because the FPGAs new DSP/tensor is implemented in a fine-grained architecture, it provides the FPGA designer the ability to tune for higher performance or lower power consumption, using the minimum amount of FPGA resources for the desired algorithm. Agilex™ 5 devices – AI key figures of merit: Tensor neural acceleration performance: Up to 26 / 56 TOPS ² Better performance per power efficiency versus embedded market inference GPUs. 1.7x higher frames per second per watt ³ Better raw performance versus other AI targeted FPGAs. 69% higher frames per second ⁴ There are many great reasons to look at this new family of FPGAs. If you are an architect, AI developer, or FPGA designer for embedded systems, don’t wait. As Mark Twain famously said, “The secret of getting ahead is getting started.” Don’t believe the marketing hype, try out your ideas in actual hardware, to see what is ‘possible’. Agilex™ 5 SoC FPGAs are just the latest phase in our DSP/AI journey. Altera, accelerating innovators. Come visit us at Embedded World 2024: Altera booth Hall 5, 5-135 and 5-136. Footnotes: Performance per watt: https://edc.intel.com/content/www/us/en/products/performance/benchmarks/agilex-fpga/ Theoretical peak INT8 calculations for the largest density Agilex 5 E-Series or D-Series devices. 1.7x higher frames per second per watt vs. Nvidia Jetson-class GPUs (AGX Orin) 69% higher frames per second vs. AMD/Xilinx Versal AI devices (VE2302)
1 month ago1like