A customizable platform for FPGA adaptation & resilience
Variation and latent defects force sign-off to guardband every device for the slowest silicon at the worst-case corner. That conservatism costs performance and energy, and it still misses the defects that fail in the field. Fluid Silicon measures every device at speed, in-system, exposes those defects and keeps each device inside its measured margin.
AMD and Altera devicesNo RTL changesRead-only by defaultDeployed on-premises
| Site | Element | Slack | Time to threshold | Status |
|---|---|---|---|---|
| X84Y212 | C6LUT | 8.2% | 1.4 yrs | Action |
| X85Y212 | Carry | 9.6% | 2.2 yrs | Watch |
| X40Y96 | B5LUT | 11.9% | 2.8 yrs | Watch |
In the field
One cause: variation and latent defects make each device's real margin different, and nothing measures it after sign-off. That margin varies across the die and shrinks with temperature and age. Monitoring is read-only; tuning and repair are separate steps you enable.
A path that closed timing at sign-off slows with temperature and aging until it violates setup in the field. A time-to-threshold per element schedules the fix before it fails.
Reliability, Availability, ServiceabilityErrors that disappear on the bench close as no fault found. Measured slack per LUT and carry chain gives every error a location on the die.
Failure Prediction & DiagnosticsSame part number, same speed grade, different silicon. Measure every board at incoming inspection and know which ones sit near their timing limit.
Card QualificationHealthy boards come out on a schedule while marginal ones stay in. Keep each board in service on its measured slack and retire the rest on evidence.
Lifecycle & Second LifeVariation and latent defects force every device onto a guardband sized for the slowest silicon at the worst-case corner. Once each device is monitored, the excess is recovered within its measured margin, never past it.
Guardband RecoveryAMD and Altera devices across several nodes and board generations report health differently, if at all. One metric covers all of them: measured slack as a share of the clock period.
Fleet Deployment & OperationsThe measurement
*Fluid Silicon measurements. Varies with variation pattern, workload, vendor and device age.
How it works
A device is characterized once, against the slowest silicon at the worst-case corner, and runs on that assumption for life. Fluid Silicon adds a lightweight health layer alongside your design that measures setup slack in-system, at operating frequency, for as long as the device runs.
Setup slack on individual LUTs, carry chains and the routing between them, while your design runs. A full sweep takes about a second; each link is resolved to under 20 ps.
An aging curve fitted to each device's temperature history, with a time-to-threshold for every element on the die.
Vccint and clock follow the margin each device has measured, never past it, in maintenance windows you schedule, re-measured after every change.
Nothing in your design moves until an element degrades toward your threshold. Then only that path is re-placed onto healthy resources, through your change process.
Why now
Guardbanding every device for the slowest silicon made sense when nothing could be measured in the field. Three things have changed.
At 16, 14 and 7 nm, random variation alone exceeds 20%, on top of systematic variation and latent defects across the die. Two devices with the same part number and speed grade are less alike with every node.
Read moreBoards stay in service for six years and more, and a device in a hot enclosure ages faster than the same part in a cool one. Sign-off happens once; the silicon keeps changing.
Read moreFPGAs are reprogrammable after they ship, so a health layer can be added to devices already in service, with no new silicon. Each device's margin is measured instead of assumed from the slowest one.
Read moreMargin and precision figures are Fluid Silicon measurements and vary with variation pattern, workload, vendor and age.
Where it applies
Each industry reads the same measurement differently: as watts, as uptime, as a maintenance schedule, as evidence.
Ship cards with measured margin and a health signal for the life of the board.
Explore Board & System Makers solutionsFar-edge systems with tight power budgets and no service access.
Explore Aerospace & Defense solutionsA decade in cabinets that are rarely visited.
Explore Telecommunications solutionsInstruments whose timing has to stay exactly what it was.
Explore Test & Measurement solutionsHot, high-utilization clusters where every watt and every timing fault counts.
Explore AI / HPC solutionsMulti-vendor fleets, several board generations, years in service.
Explore Data Center & Cloud solutionsWhere this goes
A device that measures its own timing belongs wherever silicon has to be trusted. FPGAs are reprogrammable, so the health layer can be added to devices already in service, with no new silicon. That makes them the first step.
Per-element measurement on AMD and Altera devices, with evaluations that start on a few of your boards.
Each device monitored, modeled, tuned and, when needed, repaired on its own measurement: on the bench, in a vehicle, in a cabinet or in a data center.
The same per-element measurement for other silicon that has to run for years, so no system fails because a part ran out of margin unnoticed.
Who we are
Fluid Silicon is a Philadelphia company building reliability software for FPGAs. The approach comes from reconfigurable-computing research at the University of Pennsylvania.
Nhlanhla developed the approach behind Fluid Silicon through master's research at the University of Pennsylvania on online health monitoring and runtime repair for commercial FPGAs.
André has worked in reconfigurable computing for decades, at Berkeley, Caltech and, since 2006, the University of Pennsylvania, where he is the Oliver C. Boileau Jr. and Nan Eleze Boileau Professor of Electrical Engineering. His research on FPGA architecture and interconnect underpins Fluid Silicon's approach.
Victor works with the founders on Fluid Silicon's business strategy, its engagement with customers, partners and funders, and the financial analysis behind those decisions. He studied economics at the Wharton School and spent two summers at Boston Consulting Group before joining.
The University of Pennsylvania on the research behind Fluid Silicon and the President's Sustainability Prize awarded to Nhlanhla Mavuso for the project.
Penn TodayApril 2026Penn announces its 2026 prize recipients. The Sustainability Prize recognizes the work behind Fluid Silicon: running chips at their measured limits instead of a worst-case margin.
Penn TodayWhy timing models carry 30–54% margin for the worst chip in the population, why that was the right call, and what per-chip measurement changes.
ReadTemperature sets the aging rate. The same board reaches its threshold years apart in a cool rack and a hot enclosure, and now that can be measured.
ReadA worked example for 10,000 cards: the arithmetic behind adaptive voltage scaling at fleet scale.
ReadA 30-minute session: in-system slack measurements on a supported AMD or Altera device, and what an evaluation on your boards involves.