AlgoSilicon takes an algorithm from a Python or MATLAB reference all the way onto working silicon, across the host CPU, the embedded ARM, and the FPGA fabric of real radios and edge platforms. An AI-driven automation flow generates the hardware, bit-exact and timing-closed, verified at every layer. Verified FPGA IP cores are one of the things we ship. Every performance number is a measured tool result.
We close the distance between an algorithm and a working product on real hardware. The same flow serves researchers proving an idea, developers building a prototype, and engineers shipping an edge product, across wireless and 5G, satellite and space, software radio, and edge AI.
Start from a Python or MATLAB reference. An AI-driven flow restates it as a golden model, scores candidate hardware architectures on throughput, latency, and resources, and picks the one that fits your device.
The generated RTL is checked against a cycle-accurate model and the golden reference to zero least-significant bits, across the hardest realistic inputs, then placed and routed on your part with the Vivado timing and utilization reports as the record.
When a design outgrows one chip, we split it across the tiers of the platform: the rate-critical path in the FPGA fabric, data movement on the embedded ARM, the heavy back end on the host CPU. Demonstrated on an ADALM-Pluto radio over the air; we target the same method on RFSoC, USRP, and NPU/GPU accelerators.
Each core family is produced by a parameterized generator: change the code parameters and a new, bit-exact decoder or pipeline is emitted and re-verified automatically. These are the verified building blocks we deploy into real systems. You license proven silicon, and the ability to re-target it in days.
A complete 802.11a Wi-Fi receiver physical layer: synchronization, OFDM demodulation, equalization, soft demapping, and Viterbi decoding. A MATLAB-generated standard waveform is recovered bit-for-bit on a fingernail-sized FPGA.
A 5G NR cell-search receiver: primary-synchronization detection, SSB extraction, a 256-point OFDM demodulation, and the full broadcast decode to the Master Information Block. Three real over-the-air cells are read to a consistent broadcast message.
Layered and folded QC-LDPC decoders for 3GPP 5G NR (BG1/BG2, all lifting sizes), Wi-Fi, and CCSDS AR4JA deep-space links. Syndrome-based early termination, zero DSP usage, single-CNU area class.
A soft-decision Viterbi decoder for rate-1/2 convolutional codes, K=7 and K=9. One decoded bit per clock, zero DSP, and open RTL verified bit-for-bit against the reference decoder, where the common commercial core ships encrypted.
Streaming FFT engines (1k–8k points) and a 58-variant FIR filter family: symmetric, systolic, multi-channel TDM, polyphase resamplers, digital up/down-conversion chains. One sample per clock, every clock.
A hardware limit-order-book builder processing one exchange message per clock cycle, verified bit-exact against real NASDAQ market-data replay. Hierarchical symbol caching scales to full-market coverage.
Relay belief-propagation decoder for quantum error correction on bivariate-bicycle codes (the IBM "gross" code). FPGA-pipelined BP iteration already clocking past the published reference implementation.
The same automation that builds our IP works on your algorithm. We take a Python or MATLAB reference to verified, timing-closed RTL, rescue an existing design that will not close timing, and take a validated design onto real hardware.
Your signal-processing or decision algorithm, delivered as bit-exact synthesizable RTL with a full verification suite. Typical delivery 2–8 weeks.
How it worksAn automated closure flow that classifies every failing path and applies the right structural fix. Case study: a 5G LDPC decoder taken from 221 MHz to 463 MHz on the same device. MEASURED
Closure flowNew code rates, block sizes, channel counts, or target devices for any core in our catalog, regenerated and re-verified in about a week, not a redesign.
VariantsA validated design taken onto a real SDR or heterogeneous platform: partitioned across FPGA fabric, embedded ARM, and host CPU, brought up rung by rung, bit-exact on every tier. Proven on an ADALM-Pluto Wi-Fi link, over the air.
DeploymentEvery product passes a strict three-layer equivalence chain: a golden mathematical model validated against the published standard, a cycle-accurate Python model validated against the golden model, and RTL validated bit-exact against the cycle model, to zero least-significant-bit tolerance.
Performance claims follow the same discipline. If a number on this site is not a real synthesis, place-and-route, or simulation result, it is labeled a target.
Inside the methodology
Every figure on this site traces to a tool report: a Vivado timing summary, a utilization report, or a cycle-accurate simulation log. Numbers we have not yet measured are explicitly badged as targets. Ask us for the evidence behind any claim and we will show you the report.