Abstract: Resource estimation for implementing circuit designs in an integrated circuit (IC) can include detecting, using computer hardware, a plurality of Intellectual Property (IP) cores within a circuit design, extracting, using the computer hardware and from the circuit design, parameterizations for the plurality of IP cores as used in the circuit design, and selecting, using the computer hardware, a machine learning (ML) model corresponding to each IP core, wherein each selected ML model is specific to the corresponding IP core. Each selected ML model can be provided input specifying a target IC for the circuit design and the parameterization for the corresponding IP core. An estimate of resource usage for the circuit design can be generated by executing the selected ML models. The resource usage specifies an amount of resources of the target IC needed to implement the circuit design in the target IC.

Abstract: Multiplication of integers over a finite field involves an array of arithmetic circuits configured to input a-limbs, d-limbs, and r-limbs. The array determines an intermediate term, Z, having z-limbs 0 through Kby determining respective sets of intermediate z-limbs 0 through K- 1 for r-limbs i for i = 0 to K - 1, and summing corresponding ones of the intermediate z-limbs of sets i through K - 1. The arithmetic circuits determine for r-limb 0, intermediate z-limbs 0 through K - 1 of set 0 as products of r-limb 0 and a-limbs 0 through K - 1, and for the remaining r-limbs determines intermediate z-limbs using different combinations of a-limbs, r-limbs, modulus, and d-limbs. A modulo circuit computes G as (most significant M bits of Z* m) + (least significant Q bits of Z, wherein M is a number of bits by which a number of bits of Z exceeds N, and Q is equal to M + ceil (log2 m), and increases G by m if bits Q through N - 1 of Z all having bit value one, and G ? 2Q - m.

Abstract: Implementing an application within an integrated circuit (IC) having a data processing engine (DPE) array coupled to a Network-on-Chip (NoC) can include determining, using computer hardware, data transfer requirements for a software portion of the application intended to execute on the DPE array by simulating data traffic to the NoC as generated by the software portion, generating, using the computer hardware, a NoC routing solution for data paths of the application implemented by the NoC based, at least in part, on the data transfer requirements for the software portion. The software portion can be compiled for execution by different ones of a plurality of DPEs of the DPE array based, at least in part, on the NoC routing solution. Configuration data can be generated using the computer hardware. The configuration data, when loaded into the IC, configures the NoC to implement the NoC routing solution.

Abstract: Training of a machine learning model used to infer estimated delays of circuit routes during placement and routing of a circuit design. Training can include selecting sample pairs of source pins and destination pins of an integrated circuit (IC) device, and determining respective delays of shortest paths that connect the source pins to the destination pins of the sample pairs based on a resistance-capacitance model of wires that form the shortest paths on the IC device. Respective sets of features are determined for the shortest paths, and the model is trained using the respective sets of features and the respective delays as labels. The machine learning model can be provided to an electronic design automation tool for estimating delays.

Abstract: An integrated circuit (IC) can include a plurality of circuit blocks, wherein each circuit block includes design for testability (DFT) circuitry. The DFT circuitry can include a scan interface, wherein each scan interface is uniform with the scan interface of each other circuit block of the plurality of circuit blocks, an embedded deterministic test circuit coupled to the scan interface, wherein the embedded deterministic test circuit couples to circuitry under test, and a scan response analyzer coupled to the scan interface. The scan response analyzer is configured to operate in a selected scan response capture mode selected from a plurality of scan response capture modes. The IC can include a global scan router connected to the scan interfaces of the plurality of circuit blocks. The global scan router is configured to activate a subset of the plurality of circuit blocks in parallel for a scan test.

Abstract: Examples herein describe an acceleration framework that includes a hybrid congestion control (CC) engine where some components are implemented in software (e.g., a CC algorithm) while other components are implemented in hardware (e.g., measurement and enforcement modules and a flexible processing unit). The hardware components can be designed to provide measurements that can be used by multiple different types of CC algorithms. Depending on which CC algorithms are currently enabled, the hardware components can be programmed to perform measurement, processing, and enforcement tasks, thereby freeing the CPUs in the host to perform other tasks. In this manner, the hybrid CC engine can have the flexibility of a pure software CC algorithm with the advantage of performing many of the operations associated with the CC algorithm in hardware.

Abstract: A device includes a data processing engine array having a plurality of data processing engines organized in a grid having a plurality of rows and a plurality of columns. Each data processing engine includes a core, a memory module including a memory and a direct memory access engine. Each data processing engine includes a stream switch connected to the core, the direct memory access engine, and the stream switch of one or more adjacent data processing engines. Each memory module includes a first memory interface directly coupled to the core in the same data processing engine and one or more second memory interfaces directly coupled to the core of each of the one or more adjacent data processing engines.

Abstract: A method for measuring asynchronous timestamp requests includes receiving a timestamp (“TS”) request from a client device during a first interval of a time of day (“TOD”) clock, and calculating, using the TOD clock, at a next interval of the TOD clock, a TS correction of the TS request relative to a reference point of the first TOD clock interval. The method further includes adding the TS correction to the reference point of the first interval of the TOD clock, and outputting the corrected TS to the client device.

Abstract: Embodiments herein describe on-demand packetization where data that is too large to be converted directly into data words (DWs) for a chip-to-chip (C2C) interface are packetized instead. When identifying a protocol word that is larger than the DW of the C2C interface, a protocol layer can perform packetization where a plurality of protocol words are packetized and sent as a transfer. In one embodiment, the protocol layer removes some or all of the control data or signals in the protocol words so that the protocol words no longer exceed the size of the DW. These shortened protocol words can then be mapped to DWs and transmitted as separate packets on the C2C. The protocol layer can then collect the portion of the control data that was removed from the protocol words and transmit this data as a separate packet on the C2C interface.

Abstract: Transformer based voltage controlled oscillator circuitry for phase-locked loop circuitry includes upper band circuitry and lower band circuitry. The upper band circuitry operates in a first frequency range and includes a first capacitor array having a variable capacitance. The lower band circuitry operates in a second frequency range and includes a second capacitor array having a variable capacitance. The first frequency range higher than the second frequency range. In a first operating mode, the first capacitor array has a first capacitance value and the second capacitor array has a second capacitance value. In a second operating mode, the second capacitor array has a third capacitance value different than the second capacitance value.

Abstract: Computer-based simulation of a device under test (DUT) corresponding to a user circuit design includes providing an adapter configured to couple to the DUT during the computer-based simulation (simulation). The adapter is configured to translate incoming high-level programming language (HLPL) transactions into DUT compatible data for conveyance to the DUT and translate DUT compatible data generated by the DUT to outgoing HLPL transactions. A communication server is provided that couples to the adapter during the simulation. The communication server is configured to exchange the incoming and outgoing HLPL transactions with an entity executing external to the simulation. A communication layer client is provided that is configured to execute external to the simulation and exchange the incoming and outgoing HLPL transactions with the communication server.

Abstract: Disclosed approaches for accumulating pre-carry data include initializing hold sum to a sum of a LSB of the first pre-carry word of an input stream and an MSB of a second pre-carry word by a pre-carry processing circuit. For successive pre-carry words, the LSB of pre-carry word i and the MSB of pre-carry word i+1 are summed into a next sum. An FFcount is incremented by an adder circuit if the LSB of the next sum is equal to 0xFF. If the LSB of the next sum is not equal to 0xFF, the pre-carry processing circuit outputs either: the hold sum followed by FFcount consecutive 0xFF values, if the MSB of the next sum is equal to 0x00, or the hold sum plus one, followed by FFcount consecutive 0x00 values, if the MSB of the next sum is not equal to 0x00. If the LSB of the next sum is not equal to 0xFF, the hold sum is updated with the LSB of the next sum, and the FFcount is reset to 0. Processing repeats for successive pre-carry words in the stream.

Abstract: Computer-based simulation of a device under test (DUT) corresponding to a user circuit design includes providing an adapter configured to couple to the DUT during the computer-based simulation (simulation). The adapter is configured to translate incoming high-level programming language (HLPL) transactions into DUT compatible data for conveyance to the DUT and translate DUT compatible data generated by the DUT to outgoing HLPL transactions. A communication server is provided that couples to the adapter during the simulation. The communication server is configured to exchange the incoming and outgoing HLPL transactions with an entity executing external to the simulation. A communication layer client is provided that is configured to execute external to the simulation and exchange the incoming and outgoing HLPL transactions with the communication server.

Abstract: Circuit design simulation and clock event reduction may include detecting, using computer hardware, a plurality of models of a circuit design driven by a clock source by parsing the circuit design. The circuit design is a mixed language circuit design including a hardware description language (HDL) model and a high-level programming language (HLPL) model. Using the computer hardware, a clock requirement for the HLPL model for a simulation of the circuit design may be determined. The clock requirement of the HLPL model differs from a clock requirement of the HDL model. Using the computer hardware, an interface of the HLPL model may be modified based on the clock requirement of the HLPL model.

Abstract: In the disclosed methods and systems for processing in a neural network system, a host computer system writes a plurality of weight matrices associated with a plurality of layers of a neural network to a memory shared with a neural network accelerator. The host computer system further assembles a plurality of per-layer instructions into an instruction package. Each per-layer instruction specifies processing of a respective layer of the plurality of layers of the neural network, and respective offsets of weight matrices in a shared memory. The host computer system writes input data and the instruction package to the shared memory. The neural network accelerator reads the instruction package from the shared memory and processes the plurality of per-layer instructions of the instruction package.

Abstract: Apparatus and associated methods relate to predicting various transient output waveforms at a receiver's output after an initial neural network model is trained by a receiver's transient input waveform and a corresponding transient output waveform. In an illustrative example, the machine learning model may include an adaptive-ordered auto-regressive moving average external input based on neural networks (NNARMAX) model designed to mimic the performance of a continuous time linear equalization (CTLE) mode of the receiver. A Pearson Correlation Coefficient (PCC) score may be determined to select numbers of previous inputs and previous outputs to be used in the neural network model. In other examples, corresponding bathtub characterizations and eye diagrams may be extracted from the predicted transient output waveforms. Providing a machine learning model may, for example, advantageously predict various data patterns without knowing features or parameters of the receiver or related channels.

Abstract: An electronic system includes a mapping circuit configured to receive input samples of a dataset within a defined range of values. The mapping circuit is configured to perform comparisons that compare each input sample to each of a plurality of comparison values selected from the defined range of values. For each comparison, the mapping circuit generates an indication value specifying whether the input sample used in the comparison is greater than or equal to the comparison value used in the comparison. The system includes an adder circuit configured to generate a sum of the indication values for each comparison value and a memory configured to maintain counts corresponding to the comparison values. The counts are updated by the respective sums. The system includes a threshold detection circuit configured to determine, for the dataset, a threshold value or threshold range based on the counts read from the memory.

Abstract: Using scalable scribe regions for implementing a user circuit design includes generating a scribe region having a plurality of contours for a static top design of a circuit design for an integrated circuit. The static top design is configured to integrate with a user circuit design in the integrated circuit. Each contour defines a different size of the scribe region having a boundary that extends outward in at least one direction from a boundary of a floorplan area of the static top design on the IC. The scribe region can be translated into design constraints defining the plurality of contours of the scribe region and restrict placement of components of the user circuit design within the scribe region as sized according to a selected contour. The static top design and the plurality of design constraints can be stored in a memory for use in implementing the user circuit design.

Abstract: A neural network system includes an input layer, one or more hidden layers, and an output layer. A first layer circuit implements a first layer of the one or more hidden layers. The first layer includes a first weight space including one or more subgroups. A forward path circuit of the first layer circuit includes a multiply and accumulate circuit to receive an input from a layer preceding the first layer; and provide a first subgroup weighted sum using the input and a first plurality weights associated with a first subgroup. A scaling coefficient circuit provides a first scaling coefficient associated with the first subgroup, and applies the first scaling coefficient to the first subgroup weighted sum to generate a first subgroup scaled weighted sum. An activation circuit generates an activation based on the first subgroup scaled weighted sum and provide the activation to a layer following the first layer.

Abstract: Some examples described herein relate to packet identification (ID) assignment for a routing network in a programmable integrated circuit (IC). In an example, a design system includes a processor and a memory coupled to the processor. The memory stores instruction code. The processor is configured to execute the instruction code to construct an interference graph based on routes of logical nets through switches in a routing network, and assign identifications to the routes comprising performing vertex coloring of vertices of the interference graph. The interference graph includes the vertices and interference edges. Each vertex represents one of the logical nets having a route. Each interference edge connects two vertices that represent corresponding two logical nets that have routes that share at least one port of a switch. The identifications correspond to values assigned to the vertices by the vertex coloring.