XCVU13P-2FHGB2104I: Physical AI Starts with Fast Sensor I/O
Title: XCVU13P-2FHGB2104I: Physical AI Starts with Fast Sensor I/O | Category: Industry Applications & Solutions | Author: Klaus·Fische
XCVU13P-2FHGB2104I is an industrial Virtex UltraScale+ FPGA in the verified FHGB2104 package, which exposes 76 of the VU13P device's 128 GTY channels. The device also provides 12,288 DSP slices and 502.8 Mb across distributed RAM, block RAM and UltraRAM. Those resources can support deterministic sensor ingress and preprocessing before a host or GPU, provided the design closes lane mapping, clocks, memory flow, board signal integrity and thermal limits.
Catalog
- Define physical AI as a data-path problem
- Establish the exact device and package boundary
- Budget lanes, clocks, timestamps and package skew
- Partition deterministic preprocessing and local memory
- Design the PCIe or peer bridge to the GPU
- Qualify simultaneous I/O, power and thermal behavior
- Compare the fixed five-model set without replacement claims
Key Takeaways
- XCVU13P provides 128 GTY channels at device level, but AMD's package guide lists 76 for FHGB2104. The exact-package number controls this OPN's lane plan, and protocol, clocks, SI, PI, power and concurrency further reduce usable throughput.
- Its 12,288 DSP slices and 3,780K logic cells can support deterministic front-end processing, but no device resource count proves a particular robotics or physical-AI workload.
- The listed 48.3 Mb distributed RAM, 94.5 Mb block RAM and 360 Mb UltraRAM sum arithmetically to 502.8 Mb, about 62.9 MB. They have different structures and are not one uniform pool; at high ingress rates they still represent a short local working window.
- The confirmed FHGB2104 package and 259 ps package-skew figure belong in the lane-alignment budget. They are not reasons to omit board skew, clock uncertainty or protocol deskew.
- XCVU13P is not an HBM FPGA. HBM literature can motivate memory hierarchy, but it cannot be used to claim integrated HBM on this OPN.
Physical AI Begins Before the Model
Physical AI systems turn observations from cameras, lidar, radar, microphones, encoders, force sensors or industrial instruments into timely actions. The machine-learning model is only one stage. Before inference, the system must receive each stream, preserve identity and timing, detect corruption, normalize formats and move data into an accessible memory domain. A missed frame or ambiguous timestamp cannot be reconstructed by a larger GPU after the fact.
That makes sensor I/O an architectural contract. Each input needs a physical standard, lane count, line rate, framing method, clock source, allowable skew, error response and maximum backpressure interval. The contract should also define whether timestamps are created at the electrical boundary, at frame detection or after buffering. Those choices determine whether downstream fusion compares observations from the same physical instant.
An FPGA can be valuable because its interface logic, timestamp engines, filters and schedulers execute concurrently with bounded pipelines. Yet “deterministic” must be measured. It means the design has declared latency components, bounded queue depth, controlled clock crossings and observable fault behavior. It does not mean every path always has one-cycle latency or that a large FPGA automatically meets deadlines.
The XCVU13P-2FHGB2104I role considered here is therefore generic and architectural: a high-rate sensor ingress and preprocessing layer feeding a host, accelerator or GPU. It is not a statement that AMD specifies this exact OPN for a named robot, autonomous platform or product. The application engineer must qualify the actual protocols, IP, board and environment.
Establish the Exact Device and Package Boundary
AMD's UltraScale+ product selection guide lists VU13P with 3,780K system logic cells, 3,456K flip-flops, 1,728K LUTs, 48.3 Mb of distributed RAM, 94.5 Mb of block RAM, 360 Mb of UltraRAM and 12,288 DSP slices. It also lists four PCIe Gen3 x16 integrated blocks, eight 150G Interlaken blocks, twelve 100G Ethernet blocks with KR4 RS-FEC, 832 maximum single-ended HP I/O and a device inventory of 128 GTY channels at up to 32.75 Gb/s.
These are device resources, not an implemented sensor appliance or a package pinout. AMD UG575 lists 76 GTY channels for XCVU13P-FHGB2104; the 128-channel total is exposed only by other packages such as FLGA2577 and FSGA2577. The exact order code adds the -2 speed grade, FHGB2104 package and industrial suffix. The supplied AMD material declaration explicitly names XCVU13P-FHGB2104 and reports an average package weight of 42.9679 g. The supplied lead-free bump PCN also lists this device-package combination while stating no change to reliability, form, fit or function.
| Attribute | Verified value | Physical-AI relevance | Boundary |
|---|---|---|---|
| System logic cells / LUTs | 3,780K / 1,728K | Parallel protocol, routing and control pipelines | Usable capacity depends on placement, timing and reserved infrastructure |
| DSP slices | 12,288 | Filtering, calibration, coordinate transforms and quantized preprocessing | Operation rate depends on precision, clock, cascade use and routing |
| Distributed RAM | 48.3 Mb | Small local buffers and tables implemented in LUT resources | Shares fabric resources and is not interchangeable with block RAM or UltraRAM |
| Block RAM | 94.5 Mb | FIFOs, line buffers and small tables | Port structure and contention limit usable bandwidth |
| UltraRAM | 360 Mb | Larger windows, queues and intermediate feature storage | Capacity does not replace a sustained external-memory path |
| Listed memory-class sum | 502.8 Mb, approximately 62.9 MB | Upper capacity inventory for local working sets | Arithmetic sum, not a uniform pool; not integrated HBM |
| GTY transceivers | 128 device / 76 in FHGB2104, up to 32.75 Gb/s | High-rate sensor, network or peer ingress | Exact package exposure, legal protocols and board margin control usable rate |
| Single-ended HP I/O | Up to 832 | Parallel control, memory and sensor-side interfaces | Exact pinout and bank voltages must be checked |
| PCIe / Interlaken / 100G Ethernet | 4 / 8 / 12 integrated blocks | Host, peer and network partition options | Block counts do not prove simultaneous routed endpoints |
| Package | FHGB2104, confirmed | Board footprint, power, escape routing and cooling boundary | Use current package files; similar 2104 codes are not interchangeable |
| Package skew | 259 ps | Input to deskew and timing analysis | Must be combined with board, connector, clock and protocol skew |
Table 1: XCVU13P device resources and exact-package design boundaries | Source: AMD UltraScale+ FPGA Product Selection Guide and supplied FHGB2104 documents | Compiled by: icallin.com
The source boundary matters. Three supplied FHGB2104 material PDFs are byte-identical and therefore count as one declaration, not three independent confirmations. Another supplied declaration names FLGA2577; it is useful only as evidence that XCVU13P exists in multiple package constructions. It cannot prove a property of FHGB2104. Likewise, thermal examples for FIGD2104 or FSGA2577 in XAPP1301 must not be pasted into an FHGB2104 mechanical drawing.
Turn 76 Package-Exposed GTY Lanes into a Real Sensor-Ingress Plan
The device-level multiplication of 128 by 32.75 Gb/s produces 4,192 Gb/s, or 524 GB/s, but it is not the boundary for this OPN. FHGB2104 exposes 76 GTY channels, whose corresponding raw one-direction arithmetic is 2,489 Gb/s, or about 311.1 GB/s. Even that smaller number is neither a measured aggregate nor payload rate. It assumes every exposed lane reaches its ceiling simultaneously before protocol, board and implementation losses.
First group lanes by actual protocol. A camera interface, Ethernet link, optical peer or proprietary converter specifies a legal lane count and encoding. Each group consumes reference clocks, transceiver quads, physical pins and board routes. Reserve lanes for redundancy, debug or future variants only if the package and placement plan makes them real. A lane that is present in the device table but blocked by another hard-IP placement is not available contingency.
Second separate line rate from payload. Encoding, FEC, frame headers, inter-packet gaps and idle symbols reduce useful sensor data. A 32.75 Gb/s serial ceiling is not 4.094 GB/s of application pixels without qualification. Image blanking, metadata, packetization and retransmission may raise or lower instantaneous demand relative to average pixel payload. The bandwidth sheet should preserve each layer rather than hiding it in an “efficiency” constant with no source.
Third define concurrency. Physical-AI systems often have burst alignment: multiple cameras expose together, radar frames arrive on a schedule, and control sensors produce interrupt-driven events. Average bandwidth can fit while simultaneous bursts overflow one arbitration point. Use worst-case phase alignment and maximum legal frame size, then validate with traffic generators that reproduce it.
| Reference case | Arithmetic | Result | Correct interpretation |
|---|---|---|---|
| One GTY ceiling | 32.75 Gb/s divided by 8 | 4.094 GB/s raw | Before encoding, FEC, framing and board margin |
| 16-lane group | 16 x 32.75 Gb/s | 524 Gb/s raw | Planning ceiling for a hypothetical legal group, not payload proof |
| FHGB2104 exposure | 76 x 32.75 Gb/s | 2,489 Gb/s or 311.1 GB/s raw | Exact-package arithmetic ceiling; still not payload or simultaneous-operation proof |
| VU13P device inventory | 128 x 32.75 Gb/s | 4,192 Gb/s or 524 GB/s raw | Device comparison only; FHGB2104 does not expose all 128 channels |
| Listed memory-class sum | 502.8 Mb divided by 8 | 62.85 MB | Arithmetic capacity before class, port and placement allocation |
| Retention at FHGB2104 arithmetic | 62.85 MB divided by 311.1 GB/s | about 202 microseconds | Ideal upper reference; a real queue receives only one portion of the memory |
| Package skew relative to one 32.75 Gb/s unit interval | 259 ps divided by about 30.5 ps | about 8.5 unit intervals | Demonstrates why deskew is mandatory; not a timing-closure result |
Table 2: Sensor-ingress rate, storage and skew planning references | Source: AMD verified values plus explicit unit conversions | Compiled by: icallin.com
The 259 ps package-skew value is especially important. At 32.75 Gb/s one unit interval is about 30.5 ps, so 259 ps spans roughly 8.5 unit intervals. That comparison does not mean data simply arrives 8.5 bits late at a protocol endpoint; transceivers recover and align data according to their architecture. It shows why package skew must be included in the complete alignment budget rather than treated as negligible.
Board trace mismatch, connector variation, cable or optical latency, recovered-clock behavior and protocol marker spacing add to the problem. The correct deskew mechanism depends on the interface. It may live in a PCS, an elastic buffer, a framing layer or application logic. The design needs a maximum supported skew, buffer-depth proof, acquisition time, loss-of-alignment alarm and recovery policy.
Make Timestamping and Preprocessing Deterministic
Timestamp location defines meaning. A timestamp applied when a DMA descriptor reaches host memory measures software delivery, not sensor exposure. A timestamp applied at the first recognized frame boundary is closer to ingress, but still includes sensor serialization and link latency. For multi-sensor fusion, document the physical event represented, clock domain, epoch, resolution, drift and calibration method.
A practical FPGA front end often maintains a common time base and captures local counters near each ingress block. Cross-domain logic transfers timestamp and frame identity together, with formal CDC review. Calibration can estimate fixed link offsets, while monitoring detects drift or discontinuity. On clock loss, the system should mark data invalid rather than quietly continue with stale time.
Preprocessing should reduce or regularize data while preserving provenance. Examples include bad-pixel correction, color or range normalization, finite-impulse-response filtering, region extraction, coordinate conversion, packet validation and compression preparation. XCVU13P's 12,288 DSP slices make deeply parallel arithmetic possible, but the implemented precision and routing decide real throughput. An INT8 headline, floating-point operation or DSP count should never substitute for synthesis and post-route evidence for the chosen algorithm.
The pipeline must carry metadata with samples: sensor ID, timestamp, frame number, calibration version, error flags and data-format tag. If payload is cropped or transformed, record enough information to interpret the output. This is not administrative overhead. Physical-AI debugging depends on knowing whether a bad decision came from the environment, the sensor, link corruption, time misalignment, preprocessing or the model.
| Pipeline stage | Input contract | Deterministic work | Output and proof obligation |
|---|---|---|---|
| Physical receive | Named protocol, lanes, clocks and electrical limits | CDR, equalization, alignment and error detection | Stable link, margin evidence and visible fault counters |
| Frame acquisition | Valid blocks plus protocol markers | Delimit frames, validate headers and assign identity | Frame sequence, integrity status and repeatable recovery |
| Timestamping | Frame event and local/common clock | Capture time, cross domains and apply calibrated offset | Defined epoch, resolution, bounded error and invalid-time indication |
| Preprocessing | Typed samples and calibration metadata | Filter, normalize, transform, crop or aggregate | Bit-accurate vectors, bounded latency and overflow behavior |
| Local buffering | Payload, metadata and downstream credits | Absorb bursts and arbitrate flows | Occupancy limits, priority policy, drop counters and backpressure proof |
| Host/GPU bridge | Scheduled buffers and descriptors | Packetize, DMA and signal completion | Sustained throughput, latency distribution and recovery from stalls |
| System supervision | Counters, alarms and thermal/power telemetry | Apply policy, isolate faults and preserve evidence | Reproducible event log without software in the line-rate path |
Table 3: Deterministic physical-AI sensor-front-end pipeline | Source: AMD device capabilities and system architecture analysis | Compiled by: icallin.com
Use 502.8 Mb Across Memory Classes as a Working Set
The arithmetic sum of 48.3 Mb distributed RAM, 94.5 Mb block RAM and 360 Mb UltraRAM is 502.8 Mb, about 62.85 MB. That inventory can be transformative for deterministic line buffers, sliding windows, reorder queues, lookup tables and small intermediate features, but the classes have different ports, placement and implementation costs. At a hypothetical 64 GB/s aggregate, the idealized sum represents about 0.98 ms; at 128 GB/s it is about 0.49 ms; at the 76-lane package arithmetic it is about 0.20 ms. Actual queue retention is lower because no single queue can automatically consume every class at full bandwidth.
Allocate memory by function. Block RAM can suit numerous narrow FIFOs and tables. UltraRAM can suit deeper sequential buffers. Port width, clock rate, read/write concurrency and placement are as important as capacity. A planner should reserve diagnostic history deliberately instead of discovering that line buffers consumed every block needed for post-fault capture.
External memory extends capacity but adds variable latency and arbitration. Define whether raw frames, preprocessed tensors or selected events leave the FPGA. If every input is written and later read, the memory fabric can see roughly twice the ingress traffic before metadata and refresh. Compression may reduce average volume while increasing burstiness and compute. Measure the production access pattern rather than a long sequential benchmark.
The supplied WP485 explains why bandwidth-intensive systems can outgrow traditional external DDR and why AMD created separate Virtex UltraScale+ HBM devices. It is relevant as memory-hierarchy background. It is not evidence that XCVU13P includes HBM. AMD's product selection guide places VU13P in the non-HBM Virtex UltraScale+ table; HBM devices have other names and explicit HBM DRAM and AXI-interface rows.
The corrected comparison is between device inventory and exact-package exposure. VU13P's 128-channel device inventory corresponds to 4,192 Gb/s raw one-direction arithmetic, while the 76 channels exposed through FHGB2104 correspond to 2,489 Gb/s. Neither value is an application net-throughput claim. Both omit encoding, FEC, framing, idles, protocol behavior, board margin and workload constraints, and neither proves that memory or the host path can sustain useful traffic.
This distinction guides the board. If the workload needs more sustained capacity than on-chip memory provides, architect an external DDR-class path or move reduced data to host/GPU memory. If integrated HBM is a true requirement, select and qualify an HBM device rather than relabeling VU13P. The decision affects package, power, thermal design, tools, cost and availability, so it belongs at architecture review.
Bridge to the GPU Without Moving the Bottleneck
VU13P lists four integrated PCIe Gen3 x16 blocks. That is a useful host-interface inventory, but a physical-AI architecture still needs a routable package and board topology, legal endpoint configuration and measured DMA path. Protocol overhead, descriptor size, host memory, NUMA placement, IOMMU behavior and software scheduling influence sustainable delivery.
Define the bridge payload. A sensor front end might send every raw frame, normalized pixels, regions of interest, sparse events or compact feature tensors. Each choice changes bandwidth, latency, reproducibility and where algorithms can evolve. Moving preprocessing into the FPGA can reduce traffic and jitter, but it also fixes more behavior in the bitstream and creates a verification obligation.
Backpressure is unavoidable. The GPU may pause during kernel scheduling, memory contention, error recovery or application synchronization. The FPGA needs credits or bounded queues and a declared response when the pause exceeds capacity: drop newest, drop oldest, reduce quality, stop acquisition or isolate one sensor. Silent overwriting destroys causal evidence.
Completion signaling should preserve sensor identity and time. A host descriptor needs buffer address and length plus frame number, timestamp, format, calibration revision and error state. Batch size may improve throughput but increase latency. Measure both average and tail latency, because control systems often fail on rare stalls rather than average performance.
Qualify the Whole Front End in Stages
Start with exact identity and package documentation. Confirm the XCVU13P-2FHGB2104I marking/traceability record, board revision, pinout, bank voltages, power rails, clock sources and configuration image. The material declaration and XCN23007 support package construction and change-control context; they do not replace the pinout or electrical data sheet.
Measure rails and clocks before loading all transceivers. Capture startup, configuration and traffic transients. Validate reference-clock jitter and distribution. Establish temperature sensing and cooling pressure using package-specific mechanical guidance. XAPP1301 is valuable for general flip-chip thermal discipline, but exact lid and heat-sink instructions must match FHGB2104 rather than a different example package.
Bring up one lane and one protocol group, then scale to concurrent groups. Record error-free duration, error counts, eye or margin information, equalization and recovery. Exercise cable or optical variants, temperature and intended board population. When lane count rises, watch crosstalk, reference sharing, rail droop and junction temperature.
Then add frame detection, timestamping and preprocessing with known vectors. Inject missing markers, corrupt blocks, clock jumps and calibration changes. Check that metadata remains attached to the correct payload. Add queues and force controlled GPU stalls until thresholds and drop policies activate. Finally run the production sensor mix with host/GPU load, thermal load and long-duration fault logging.
| Qualification stage | Test focus | Required measurement | Invalid shortcut |
|---|---|---|---|
| Identity and board audit | Exact OPN, FHGB2104 pinout, banks, rails and clocks | Traceability record, schematic review and measured startup | Using FLGA2577 or another 2104 package as exact proof |
| Single-link SI | One lane and one protocol group | Margin, error counters, equalization and retraining | Treating configuration success as signal-integrity proof |
| Concurrent ingress | Intended package-exposed lane groups active together | Aggregate counters, crosstalk, rail and thermal evidence | Multiplying one-lane performance by 76 or transferring the 128-device total |
| Time and frame integrity | Markers, timestamps, CDC and fault injection | Bounded error, sequence continuity and recovery logs | Timestamping only after nondeterministic host delivery |
| Preprocessing and buffers | Bit-accurate kernels, bursts and backpressure | Latency distribution, occupancy, overflow and drop policy | Quoting DSP or memory count as achieved performance |
| Host/GPU bridge | Production DMA, descriptors and contention | Sustained payload, tail latency, stalls and recovery | Relying on PCIe block count or nominal line rate |
| Environmental sign-off | Full traffic, power and cooling corners | Post-route timing, measured rails, temperature and long-run counters | General thermal note substituted for exact assembly proof |
Table 4: Staged validation for an XCVU13P physical-AI front end | Source: AMD device and package documents plus system verification practice | Compiled by: icallin.com
Compare the Closed Five-Model Set Carefully
The related models show different architectural scales. They are not substitutes. Moving between Kintex and Virtex, UltraScale and UltraScale+, or package codes changes transceivers, pinout, power, clocks, IP support and implementation. A migration project begins again at the interface contract.
| Role | Exact model and verified page | Useful comparison | Selection boundary |
|---|---|---|---|
| Primary | XCVU13P-2FHGB2104I | 76-package-GTY sensor ingress and deterministic preprocessing subject | Exact FHGB2104, power, memory and lane validation control |
| Related 1 | XCKU060-2FFVA1156I | Smaller UltraScale partition or control comparison | Different generation, GT resources and package require redesign |
| Related 2 | XCKU115-2FLVA1760I | Larger Kintex UltraScale context | Package string requires AMD confirmation; not a compatible alternative |
| Related 3 | XCKU15P-2FFVA1156I | Kintex UltraScale+ hard-networking comparison | FFVA1156 exposes 20 GTH and 8 GTY; role and board are materially different |
| Related 4 | XCVU19P-2FSVA3824I | Very-large Virtex fabric and package comparison | Different transceiver mix, 65 mm-class package and cooling problem |
Table 5: Closed five-model physical-AI architecture comparison | Source: AMD documentation and verified ICAllin product routes | Compiled by: icallin.com
The XCKU115-2FLVA1760I package string requires AMD confirmation before any package-level decision. It is included only because it is in the approved editorial set and must not be described as a compatible alternative. XCKU15P offers a different hard-networking profile but much lower exact-package GT exposure. XCVU19P is larger in some dimensions yet changes the mechanical and high-speed problem substantially.
Use the AMD Xilinx manufacturer page to navigate the broader catalog, then return to current AMD ordering, package and electrical documents for every candidate. Sourcing navigation does not establish design compatibility.
Frequently Asked Questions
1. Is XCVU13P-2FHGB2104I an HBM FPGA?
No. XCVU13P belongs to the non-HBM Virtex UltraScale+ device table. AMD's HBM products have distinct device names and explicit HBM capacity and interface entries. The supplied HBM white paper compares an XCVU13P SSI foundation with an HBM-enabled device to explain the newer architecture; it does not put HBM inside XCVU13P.
2. Does XCVU13P-2FHGB2104I provide 128 usable GTY lanes?
No. VU13P has 128 GTY channels at device level, but AMD UG575 lists 76 for the FHGB2104 package. Multiplying 76 by 32.75 Gb/s gives 2,489 Gb/s raw one-direction arithmetic, not sensor payload. Usable throughput further depends on legal protocol grouping, encoding, FEC, framing, clocks, board loss and simultaneous-operation margin.
3. How should the 259 ps package-skew figure be used?
Include it in the timing and lane-alignment budget with board mismatch, connectors, sensor or optical latency, recovered-clock behavior and protocol limits. At 32.75 Gb/s it is roughly 8.5 unit intervals, which underscores the need for defined deskew. It is not by itself a failure, guaranteed latency or substitute for package and board timing analysis.
4. Is 502.8 Mb enough to buffer all sensor data?
It depends on rate, memory class and pause duration. The 502.8 Mb figure is an arithmetic sum of distributed RAM, block RAM and UltraRAM, about 62.85 MB, not one uniform buffer. At 64 GB/s that idealized capacity is about 0.98 ms; at the 311.1 GB/s package-exposed lane arithmetic it is about 202 microseconds. Real queues receive only part of the inventory and must respect each class's ports and placement.
5. What preprocessing belongs in the FPGA rather than the GPU?
Good FPGA candidates have bounded, streaming dataflow: link validation, timestamp capture, calibration, filtering, normalization, cropping, coordinate conversion and deterministic packet scheduling. The split should reduce transport load or jitter without freezing rapidly changing model logic unnecessarily. Verify bit accuracy, overflow, latency and metadata preservation for the actual precision and traffic mix.
6. What evidence should accompany a sourcing decision?
Specify the full XCVU13P-2FHGB2104I OPN, quantity, delivery window, traceability needs, date-code or lot constraints, package handling and documentation requirements. Confirm package identity against current AMD material, ordering and marking records. Keep the dated commercial response with the build record and do not treat it as electrical or application qualification.
Immediate Stock Alert
Availability for XCVU13P-2FHGB2104I is dynamic. Provide the exact OPN, quantity, delivery window, lot or date-code constraints, traceability and document needs through the current availability page. Revalidate the response when the build quantity or schedule changes. No fixed inventory, price or lead-time commitment is made here, and a commercial response does not qualify the FPGA, package or board for the intended sensor system.
Conclusion
XCVU13P-2FHGB2104I brings unusually large resources to a sensor front end: 76 GTY channels exposed by FHGB2104, 12,288 DSP slices, 3,780K logic cells and 502.8 Mb across three listed embedded-memory classes. The underlying VU13P device has 128 GTY channels, but that device-level inventory must not be transferred to this package. The 259 ps package-skew value makes physical implementation a first-class part of the design, not an afterthought.
The useful architecture is a chain of explicit contracts. Map legal sensor lanes and clocks, define timestamp meaning, bound deskew and CDC, verify streaming preprocessing, size each queue in time, build an honest external-memory hierarchy, and measure the PCIe or peer bridge under GPU backpressure. Validate single links before concurrency, then add power and thermal corners with reproducible counters.
Physical AI starts with fast sensor I/O because inference quality depends on timely, intact and attributable observations. XCVU13P can support that method, but resource tables do not prove a specific robot, model or throughput. The final claim belongs only to the exact bitstream, board, sensor mix, host and environmental test record.
References
- AMD UltraScale+ FPGA Product Selection Guide (DS890)
- AMD UltraScale and UltraScale+ Packaging and Pinouts Guide (UG575)
- AMD Virtex UltraScale+ Package Parameter Guidelines (DS923)
- AMD Virtex UltraScale+ FPGA family page
- AMD PK1227, Material Declaration for XCVU13P-FHGB2104, supplied as identical
第十九篇-1.pdf,-3.pdfand-4.pdf - AMD material declaration for XCVU13P-FLGA2577, supplied as
第十九篇-2.pdfand used only as a different-package boundary - AMD XCN23007, Lead-Free Bump Conversion, supplied as
第十九篇-5.pdf - AMD XAPP1301, Mechanical and Thermal Design Guidelines for Lidless Flip-Chip Packages, supplied as
第十九篇-6.pdf - AMD WP485, Virtex UltraScale+ HBM FPGA, supplied as
第十九篇-7.pdfand used only for memory-hierarchy background - XCVU13P-2FHGB2104I product page
- AMD Xilinx manufacturer page
- Current availability request
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