Agilex 3 FPGAs & SoCs: engineering solutions for power- conscious, cost-effective embedded systems
needed for both thermal and battery constraints. The operational speed reflects engineering choices that balance processing power with energy usage, enabling sophisticated algorithm implementation within practical power limitations.
AI processing integration The Agilex 3’s design embeds AI Tensor Blocks throughout the FPGA fabric, establishing a processing environment capable of handling standard digital signal processing as well as AI computations. These blocks can switch between DSP and Tensor operations, delivering a key adaptability that removes the need for additional acceleration hardware. The AI Tensor Blocks can perform matrix calculations efficiently, executing dot products within single clock cycles using various data formats such as fixed-point, INT8, FP16, FP19, FP32, BFLOAT16, and INT9. Combined with up to 368 configurable 18 x 19 multipliers, this architecture achieves a peak theoretical throughput of 2.54 TOPS for INT8 processing. This processing density simplifies system design and reduces component costs by incorporating specialized capabilities that would otherwise require additional hardware. It also benefits edge implementations requiring simultaneous real-time sensor processing or intelligent analysis. The ‘frictionless’ switching between signal processing and ML functions in one device enables design methodologies that would be challenging with separate processing components.
Image source: Altera
Embedded system designs require solutions that balance high performance with power and cost constraints. Unfortunately, standard FPGA architectures often require designers to compromise between power efficiency and computational capability. Altera’s Agilex 3 FPGA and SoC family addresses these challenges with purpose-built features that are optimized for embedded, edge, and industrial applications. They introduce targeted innovations with devices spanning from 25,000 to 135,000 logic elements while maintaining architectural benefits across the full range. The integration of AI acceleration, advanced security features, and processing capabilities, results in a platform suited for applications where every milliwatt and cost consideration matters. Advanced HyperFlex foundation Agilex 3 leverages a HyperFlex FPGA architecture, achieving substantial performance
gains through fundamental improvements in timing management and routing effectiveness. This foundation delivers fabric performance improvements up to 1.9 times, while reducing total power consumption by up to 38% compared to earlier solutions. These improvements result from core architectural changes that minimize critical path latencies and streamline routing complexity. Agilex 3 devices demonstrate exceptional integration capabilities, supporting up to 135,000 logic elements within packages measuring 12 mm x 12 mm. Their variable pitch BGA packaging strategy preserves high I/O density while conforming to conventional PCB design standards, facilitating easy deployment in space- constrained applications without requiring specialized production techniques. With fabric operation reaching 345 MHz, the Agilex 3 series delivers exceptional computational performance for real-time processing while preserving the power efficiency
Advanced connectivity architecture Agilex 3 devices offer robust communication capabilities via built-in transceivers operating at speeds up to 12.5 Gbps across four channels. These transceivers feature hardened PCIe 3.0 and 10 Gigabit Ethernet IP blocks, providing direct high- speed communication without external interface hardware. The consolidation reduces system complexity while maintaining reliable data transmission for applications including industrial automation, video processing, and measurement instrumentation. Memory interfacing uses LPDDR4 implementation which supports transfer rates up to 2,133 Mbps, offering sufficient bandwidth for embedded implementations while emphasizing power usage. This memory selection shows an emphasis on power-sensitive applications where battery performance and thermal control
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