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Beyond TCAM: Scale Packet Classification with Altera Stellar IP
3 MIN READ PACKET CLASSIFICATION | FPGA | NETWORKING + SECURITY Every packet decision starts with classification. Routers, firewalls, SmartNICs, security gateways, and service-edge platforms must determine which policy applies before traffic can be forwarded, blocked, inspected, redirected, or prioritized. TCAM earned its place in these systems because it provides predictable lookup behavior and native ternary matching for ACL and LPM workloads. But as policy databases grow, search keys widen, and rules change more frequently, the traditional approach of scaling specialized ternary memory creates tougher tradeoffs in capacity, power, resource utilization, and system integration. Altera Stellar IP takes a different approach. Instead of scaling packet classification by building ever-larger ternary-memory structures, Stellar turns classification into an optimized search problem that runs on configurable FPGA resources. The result is an FPGA-native path for large, dynamic packet-classification tables without giving up the policy semantics that made TCAM useful in the first place. TCAM scales through memory expansion. Stellar scales through search intelligence. Keep the TCAM semantics. Change the scaling model. Stellar preserves the intent of ACL, LPM, and multi-field classification, but changes how those rules are represented and searched. The Stellar Software Stack organizes policies into optimized graph structures, partitions the rule database, and continuously manages those search structures as the database evolves. The hardware then executes the search using configurable FPGA search engines while rule information is stored in conventional memory resources. Depending on the configuration, Stellar can use on-chip M20K memory, eSRAM, DDR, or HBM. That gives architects more freedom to balance throughput, capacity, latency, power, and FPGA resource use around the needs of the actual system. Use dense memory where it makes sense, and intelligence where it matters A traditional TCAM combines storage and comparison circuitry inside specialized ternary-memory arrays. That architecture delivers deterministic matching, but scaling the table means scaling the specialized comparison structure as well. Stellar separates rule storage from search execution. Ternary information can be represented as value-and-mask data in conventional memory, while graph organization and software-managed optimization direct each search toward the relevant parts of the database. As tables grow from thousands of entries toward hundreds of thousands or millions, this creates a different path for scaling capacity and power. The white paper goes deeper into why this matters, including the tradeoffs between TCAM and Stellar, the role of memory hierarchy, and a set of Stellar configurations spanning different key widths, capacities, memory resources, and projected five-tuple performance. Bring classification into the programmable datapath The value is bigger than the lookup engine itself. Stellar is designed to operate inside the FPGA alongside packet parsing, telemetry, encryption, traffic management, host-interface logic, and customer packet-processing RTL. For system architects, that means classification can become part of the same programmable platform already handling the datapath. A firewall can pair large, dynamic ACL processing with the rest of its traffic pipeline. A router can combine LPM and policy enforcement with programmable networking functions. A SmartNIC can integrate flow classification with offload and customer-specific acceleration. That system-level flexibility is especially relevant for 100GE to 400GE designs where classification must scale without consuming the platform that surrounds it. Read the full whitepaper! The full Altera white paper, “Altera's TCAM Alternative Solution for Routers and Firewall Security Equipment,” explains the architecture behind Stellar and the design choices that make it different. It covers TCAM fundamentals and scaling limits, Stellar graph-based search and software partitioning, memory-hierarchy options, configuration examples, quantitative architectural comparisons, dynamic updates, and deployment use cases across networking and security. Read the white paper See how Stellar uses search intelligence, configurable FPGA resources, and a flexible memory hierarchy to create a scalable alternative for large ACL and LPM workloads.29Views0likes0CommentsTerasic P16E-FMCP PCIE Express 3.0 compatibility issues with AMD processors
Hi I bought the Terasic P16E-FMCP to use on my Terasic Apollo S10 SOM board for PCI Express 3.0 implimentation. However after testing the included program, it did not work, so I emailed Terasic Support and they told me it was only tested on Intel CPU and it appears never tested on AMD. So they made me run a simple program called System Information Viewer from rh-software.com which tested the information sent and received from the PCI endpoint and it appears there are errors stimming back from the demo program does not natively run on AMD processors. So for the past 6 months, Terasic has been dragging there feet on this issue, telling me they will work on a solution but I must go out and purchase another computer by Intel, then run several versions of Quartus Pro, starting from 19.1, through 23.3, I must download them individually. I told them I am not doing this, I am not being paid to test out your code, I simply purchased the board direct from you for $650, and NOWHERE on the website does it publish it works only with Intel CPU. Instead they are pointing the fingers at me saying I'm delayin a resolution on this issue by not testing out there code, I told them that IS YOUR JOB! I AM NOT EMPLOYED BY TERASIC! Terasic is a partner program of Intel, they have all the means to reach out and contract a device driver writer and solve this incompatiblity issue. This is beyond my expertise. They simply won't do it. Does anyone have a solution to this problem? Why are they passing the buck at me?105Views0likes5CommentsModelSim Intel FPGA Ed. 2020.1 not updating changes to HDL File
I have ModelSim open and Quartus Prime Lite v. 22.1, while I'm simulating, I often make changes back to the Quartus, but when I reload the design into ModelSim, it cold-archives the initial HDL file and references that file instead of the changes I make in Quartus. No matter how many times I recompile the code for both the wrapper function and main entity, it always goes back to the original? How is this possible? Does ModelSim copy the file into it's own directory and simply references it? I've spent days trying to figure this out, wihtout creating a new project and adding the changed code to it, how can I force it to use the updated files?181Views0likes6CommentsQuarus Prime Installer 24.1 - Error SSL Certificate, Curlcde : 60
Hello, I've got an error during the installation of quartus prime 24.1 : During somes mounths, I uses this solution I've found on the download page. It works great until a few days ago. There s an other solution t use the 24.1 installer now ?120Views0likes9CommentsStore custom keys on SDM Agilex3
Hi I know it's possible to store encryption and siging keys on the SDM for fpga firmware decryption and authentication, but is it possible to store my own keys on it? I will use the key to decrypt my own software files on the HPS, so I need some way to send the ecrypted software to the SDM then the SDM will use the key to decrypt it and send it back. Is there any documentation or tutorial for this?EPM7064LI44-15 – Xeltek SuperPro 610P Program OK but Verify fails at address 0x50
Hello, I am trying to program an existing design on an Altera EPM7064LI44-15, PLCC44. The device is the original non-JTAG EPM7064LI44-15. I understand that this device requires an older parallel programming method or a third-party programmer. The discussion here indicates that a Xeltek programmer should support it. My setup is: pc windows 10 64bit Device: EPM7064LI44-15 Package: PLCC44 Programmer: Xeltek SuperPro 610P Software: SP610P - SUPERPRO for Windows V1.0 Xeltek adapter: SA244 Device selected: ALTERA EPM7064@PLCC44 Algorithm: 7064____ Design generated using MAX+PLUS II 10.2 Baseline Programming file: POF My programming sequence is: Erase ->Load-> POF-> Program-> Verify but Verify fails with: Chip Address : 00000050 Chip Data : A7 Buffer Address : 00000050 Buffer Data : 0F I would greatly appreciate any guidance or suggestions you can provide. Thank you in advance for your time and assistance.15Views0likes1CommentSystem Console master_read_memory fails above 7688 bytes on Agilex 5 (AXE5-Eagle)
A single master_read_memory of 7689 bytes or more never completes on an Agilex 5. It returns nothing, times out after 60 seconds, and leaves the JTAG channel closed so the next command fails too. 7688 bytes on the same master and the same address returns all 7688 values in under 0.1 second. The boundary is byte exact and repeats every time. I can reproduce this entirely with an unmodified example bitstream published by Arrow, so no design of mine is involved and there is nothing for me to send you. SETUP Board: Arrow AXE5-Eagle, device A5ED065BB32AE4SR0, IDCODE 0364F0DD Bitstream: axe5_eagle_voltage_temp.sof from https://github.com/ArrowElectronics/Agilex-5, path images/promo3/, md5 b391b9cd5226fe92fd2068ddc66f8442 That bitstream was built with Quartus Prime Pro 24.3 and reports "HPS present: FALSE", so it configures straight over JTAG with no bootloader merge and no HPS involvement. It exposes a Nios V node and a JTAG PHY master. Tools: Quartus Prime Pro 26.1.1 build 130, System Console from the same installation, Windows 10 Enterprise LTSC 21H2 Cable: Arrow USB Blaster ARA39943-TEI0004, JTAG clock pinned to 6 MHz, Altera JTAG Server running as a Windows service STEPS 1. Program the board over JTAG: quartus_pgm -c "Arrow-USB-Blaster [ARA39943-TEI0004]" -m jtag -o "p;axe5_eagle_voltage_temp.sof@1" 2. In System Console, open the JTAG PHY master and read: set m [lindex [get_service_paths master] 0] open_service master $m master_read_memory $m 0x0 7688 master_read_memory $m 0x0 7689 RESULT master_read_memory 7688 bytes -> 7688 values in 0 master_read_memory 7689 bytes -> nothing, 60.0 s, then: master_read_memory: This transaction did not complete e is giving up. After the failure the channel is closed and the next command reports "Channel closed" until the service is reopened. Recovering costs 20 to 60 seconds. WHAT I HAVE ALREADY RULED OUT Not the address. Identical behaviour reading from 0x0, 0x1000, 0x10000000 and 0x20000000, and shifting the base by 1, 2, 4 or 4092 bytes at a fixed size changes nothing. Only the requested byte count Not a timeout. Reads return in 0.0 s right up to 7688, then the very next byte fails. A timeout would show times rising as the limit approached, not an instant success becoming an outright fa Not the size of the reply. master_read_32 hands back a 45055 character answer without trouble, while master_read_memory fails while producing a 39044 character one. Not the design. The same byte boundary appears on two other unrelated bitstreams on this board, one with an HPS and one without, built with different Quartus versions. The Arrow example above is simy. master_read_32 IS NOT AFFECTED, AND HAS NO COMP On the same master and the same bitstream, master_read_32 was run at increasing sizes. Every one returned the full count, correctly, with no timeout and no channel closure: master_read_32 $m 0x0 4096 -> 4096 words, 16 kB spanned, 0.5 s master_read_32 $m 0x0 8192 -> 8192 words, 32 kB master_read_32 $m 0x0 16384 -> 16384 words, 64 kB spanned, 2.2 s master_read_32 $m 0x0 32768 -> 32768 words, 128 kB master_read_32 $m 0x0 65536 -> 65536 words, 256 kB spanned, 9.8 s That last one spans 262144 bytes, which is 34 times theead_memory cannot deliver, and it scales linearly at about0.15 ms per word with no sign of a ceiling. If the JTAG link, the Avalon bridge or the reply channel were the constraint, master_read_32 would degrade somewhere across that range. It does not. master_read_32 is therefore a usable workaround, but a slow one: master_read_memory returns 7688 bytes in under 0.05 s, roughly 150 kB/s, where master_read_32 sustains about 26 kB/s. Around 6 times slowp> QUESTIONS Is 7688 bytes an intended limit for master_read_memory on Agilex 5? If so, where is it documented, and does it vary by device family? The same tool version against Arria V hardware is rock solid and sh Whatever the limit is, could an oversized request return an error immediately instead of hanging for 60 seconds and closing the channel? The silent 60 second stall is far more expensive than a reject Happy to run any additional test on this board if neede127Views0likes4CommentsBoard Test System–Stratix 10TX Development Kit
Hi everyone, I’m working with the Stratix 10 TX Signal Integrity Development Kit (DKSI1STXEA) on a Windows PC. I have followed the installation steps provided in the documentation and installed the development kit software/package as instructed. However, after completing the installation, I still cannot find the Board Test System (BTS) files. According to the user guide, I expected to find something similar to: <package_dir>\examples\board_test_system\BoardTestSystem.exe I have not been able to locate the associated .sof test designs either. Has anyone successfully installed and used the BTS for this development kit? Could someone please clarify which package needs to be installed to get the BTS files, or where these files are located in the current version of the development kit software? Board: Stratix 10 TX Signal Integrity Development Kit Kit: DKSI1STXEA Host OS: Windows I have already followed the documented installation procedure, but the BTS files still appear to be missing. Any help would be appreciated. Thank you!Solved127Views0likes6CommentsAltera SSLC License
Hello, I am having issues with the Altera / Intel Self Service License Center. According to the help available online ,I should have several options in the "Licenses" menu, yet these ones are missing on my portal (Chrome, Edge, Safari: tried all latest browsers): New Licenses Licenses With Active Maintenance Licenses With Expired Maintenance All Licenses Legacy Licenses Employee and Evaluation License What is also missing seems to be the License Assistant. The blue chat button is nowhere to be found (and I tried all the pages on SSLC). https://docs.altera.com/r/docs/683472/26.1/altera-fpga-software-installation-and-licensing/using-the-altera-fpga-self-service-licensing-center https://docs.altera.com/r/docs/683472/26.1/altera-fpga-software-installation-and-licensing/viewing-licenses Is this a backend configuration issue? Could someone post screenshots of their SSLC, showing whether or not they have access to the hidden menus I am missing?481Views0likes18Comments
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Recent Blogs
PACKET CLASSIFICATION | FPGA | NETWORKING + SECURITY Every packet decision starts with classification. Routers, firewalls, SmartNICs, security gateways, and service-edge platforms must determine which policy applies before traffic can be forwarded, blocked, inspected, redirected, or prioritized. TCAM earned its place in these systems because it provides predictable lookup behavior and native ternary matching for ACL and LPM workloads. But as policy databases grow, search keys widen, and rules change more frequently, the traditional approach of scaling specialized ternary memory creates tougher tradeoffs in capacity, power, resource utilization, and system integration. Altera Stellar IP takes a different approach. Instead of scaling packet classification by building ever-larger ternary-memory structures, Stellar turns classification into an optimized search problem that runs on configurable FPGA resources. The result is an FPGA-native path for large, dynamic packet-classification tables without giving up the policy semantics that made TCAM useful in the first place. TCAM scales through memory expansion. Stellar scales through search intelligence. Keep the TCAM semantics. Change the scaling model. Stellar preserves the intent of ACL, LPM, and multi-field classification, but changes how those rules are represented and searched. The Stellar Software Stack organizes policies into optimized graph structures, partitions the rule database, and continuously manages those search structures as the database evolves. The hardware then executes the search using configurable FPGA search engines while rule information is stored in conventional memory resources. Depending on the configuration, Stellar can use on-chip M20K memory, eSRAM, DDR, or HBM. That gives architects more freedom to balance throughput, capacity, latency, power, and FPGA resource use around the needs of the actual system. Use dense memory where it makes sense, and intelligence where it matters A traditional TCAM combines storage and comparison circuitry inside specialized ternary-memory arrays. That architecture delivers deterministic matching, but scaling the table means scaling the specialized comparison structure as well. Stellar separates rule storage from search execution. Ternary information can be represented as value-and-mask data in conventional memory, while graph organization and software-managed optimization direct each search toward the relevant parts of the database. As tables grow from thousands of entries toward hundreds of thousands or millions, this creates a different path for scaling capacity and power. The white paper goes deeper into why this matters, including the tradeoffs between TCAM and Stellar, the role of memory hierarchy, and a set of Stellar configurations spanning different key widths, capacities, memory resources, and projected five-tuple performance. Bring classification into the programmable datapath The value is bigger than the lookup engine itself. Stellar is designed to operate inside the FPGA alongside packet parsing, telemetry, encryption, traffic management, host-interface logic, and customer packet-processing RTL. For system architects, that means classification can become part of the same programmable platform already handling the datapath. A firewall can pair large, dynamic ACL processing with the rest of its traffic pipeline. A router can combine LPM and policy enforcement with programmable networking functions. A SmartNIC can integrate flow classification with offload and customer-specific acceleration. That system-level flexibility is especially relevant for 100GE to 400GE designs where classification must scale without consuming the platform that surrounds it. Read the full whitepaper! The full Altera white paper, “Altera's TCAM Alternative Solution for Routers and Firewall Security Equipment,” explains the architecture behind Stellar and the design choices that make it different. It covers TCAM fundamentals and scaling limits, Stellar graph-based search and software partitioning, memory-hierarchy options, configuration examples, quantitative architectural comparisons, dynamic updates, and deployment use cases across networking and security. Read the white paper See how Stellar uses search intelligence, configurable FPGA resources, and a flexible memory hierarchy to create a scalable alternative for large ACL and LPM workloads.
3 hours ago0likes
1 MIN READ
Altera has begun shipping the new Agilex® 7 M-Series R31G multi-host acceleration package, giving customers a new way to build high-bandwidth systems that connect more hosts while moving more data through the network and memory subsystem. R31G is designed for architectures where data must move quickly between the network, memory, and multiple CPUs, GPUs, or other hosts. By bringing 800G or 2x400G Ethernet together with expanded PCIe 5.0/CXL host connectivity, the package opens new possibilities for AI NICs, storage acceleration, cloud acceleration, and other high-throughput platforms. What R31G enables More network bandwidth: 800G or 2x400G Ethernet capability for high-throughput data paths. More host connectivity: Two PCIe 5.0 x16 host interfaces, or up to four independent PCIe 5.0 x8 connections, with CXL support for flexible multi-host architectures. More memory bandwidth and I/O: DDR5-6400 and LPDDR5-6400 support, up to 204.8 GBps of memory bandwidth, and 768 GPIO in a compact 56 x 45 mm package. The result is a programmable platform that can connect, accelerate, and adapt as infrastructure requirements evolve, while keeping high-speed networking, host connectivity, and memory bandwidth tightly integrated. More network bandwidth. More hosts. More memory bandwidth. One programmable platform. Learn more in the Agilex® 7 M-Series product site.
6 days ago0likes
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.
1 month 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.
1 month 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
1 month ago0likes