Altera Corporation

Intel Corporation

Gregg William Baeckler

Martin Langhammer

David Wolk Mendel

Babette Van Antwerpen

Richard Yuan

Michael David Hutton

James G Schleicher

Sergey Vladimirovich Gribok

Jinyong Yuan

Mike Hutton

Andy Louie Lee

David Lewis

Bruce B Pedersen

Sinan Kaptanoglu

Henry Kim

Rahul Saini

Robert L Sankman

Ravindranath Vithal Mahajan

Dheeraj R Subbareddy

Md Altaf Hossain

Ankireddy Nalamalpu

Bogdan Mihai Pasca

Vaughn Betz

Chris Wysocki

Pouyan Djahani

Boris Ratchev

Keith Duwel

Stephen D Brown

Terry Borer

Kevin Chan

Ian Chesal

Sean Safarpour

Yaska Sankar

Eriko Nurvitadhi

Weiqi Ding

Scott J Weber

Dipankar Das

Divya Vijayaraghavan

David Cashman

Ketan Padalia

Meghal Varia

David Neto

James G Schleicher, Ii

Dmitry Nikolai Denisenko

Jianhua Liu

Sasikanth Avancha

Yean-Yow Hwang

Sudarshan Srinivasan

Duncan Moss

Gregory Steinke

Andrei Hagiescu

Adrian Drury

Barbette Van Antwerpen

Joachim Pistorius

The present disclosure relates to an integrated circuit device that includes a plurality of vector registers configurable to store a plurality of vectors and switch circuitry communicatively coupled to the plurality of vector registers. The switch circuitry is configurable to route a portion of the plurality of vectors. Additionally, the integrated circuit device includes a plurality of vector processing units communicatively coupled to the switch circuitry. The plurality of vector processing units is configurable to receive the portion of the plurality of vectors, perform one or more operations involving the portion of the plurality of vector inputs, and output a second plurality of vectors generated by performing the one or more operations.

Vector processor architectures

A programmable device may have logic circuitry formed in a top die and memory and specialized processing blocks formed in a bottom die, where the top die is stacked directly on top of the bottom die in a face-to-face configuration. The logic circuitry may include logic sectors, logic array blocks, logic elements, and other types of logic regions. The memory blocks may include large banks of multiport memory for storing data. The specialized processing blocks may include multipliers, adders, and other arithmetic components. The logic circuitry may access the memory and specialized processing blocks via an address encoded scheme. Configured in this way, the maximum operating frequency of the programmable device can be optimized such that critical paths will no longer need to traverse any unused memory and specialized processing blocks.

Programmable logic device with fine-grained disaggregation

A method for implementing a programmable device is provided. The method may include extracting an underlay from an existing routing network on the programmable device and then mapping a user design to the extracted underlay. The underlay may represent a subset of fast routing wires satisfying predetermined constraints. The underlay may be composed of multiple repeating adjacent logic blocks, each implementing some datapath reduction operation. Implementing circuit designs in this way can dramatically improve circuit performance while cutting down compile times by more than half.

Programmable integrated circuit underlay

Techniques for designing and implementing networks-on-chip (NoCs) are provided. For example, a computer-implemented method for programming a network-on-chip (NoC) onto an integrated circuit includes determining a first portion of a plurality of registers to potentially be included in a NoC design, determining routing information regarding datapaths between registers of the first portion of the plurality of registers, and determining an expected performance associated with the first portion of the plurality of registers. The method also includes determining whether the expected performance is within a threshold range, including the first portion of the plurality of registers and the datapaths in the NoC design after determining that the expected performance is within the threshold range, and generating instructions configured to cause circuitry corresponding to the NoC design to be implemented on the integrated circuit.

High performance regularized network-on-chip architecture

A computer-implemented method for programming an integrated circuit includes receiving a program design and determining one or more addition operations based on the program design. The method also includes performing geometric synthesis based on the one or more addition operations by determining a plurality of bits associated with the one or more addition operations and defining a plurality of counters that includes the plurality of bits. Furthermore, the method includes generating instructions configured to cause circuitry configured to perform the one or more addition operations to be implemented on the integrated circuit based on the plurality of counters. The circuitry includes first adder circuitry configured to add a portion of the plurality of bits and produce a carry-out value. The circuitry also includes second adder circuitry configured to determine a sum of a second portion of the plurality of bits and the carry-out value.

Geometric synthesis

A method for implementing a multiplier on a programmable logic device (PLD) is disclosed. Partial product bits of the multiplier are identified and how the partial product bits are to be summed to generate a final product from a multiplier and multiplicand are determined. Chains of PLD cells and cells in the chains of PLD cells for generating and summing the partial product bits are assigned. It is determined whether a bit in an assigned cell in an assigned chain of PLD cells is under-utilized. In response to determining that a bit is under-utilized, the assigning of the chains of PLD cells and cells for generating and summing the partial product bits are changed to improve an overall utilization of the chains of PLD cells and cells in the chains of PLD cells.

Method and apparatus for performing multiplier regularization

Methods and apparatus for increasing the random logic utilization on a programmable device are provided. Although not completely homogeneous, the programmable device has many components that are repeated many times in an array. To help improve repeatability and packing, computer-aided design tools for compiling a circuit design for the programmable device may first lock down a synthesis cell netlist with stable naming, create location solution files (files with desired clustering granularity for stabilizing performance and reducing compile times) for selected regions of interest on the programmable device, and compose a final design with only the best solutions some of which can be imported from one location to another. Compiling a design in this way can help improve random logic utilization beyond 85% while improving circuit performance by 20% or more.

Deterministic clustering and packing method for random logic on programmable integrated circuits

The present disclosure relates generally to techniques for improving the implementation of certain operations on an integrated circuit. In particular, deep learning techniques, which may use a deep neural network (DNN) topology, may be implemented more efficiently using low-precision weights and activation values by efficiently performing down conversion of data to a lower precision and by preventing data overflow during suitable computations. Further, by more efficiently mapping multipliers to programmable logic on the integrated circuit device, the resources used by the DNN topology to perform, for example, inference tasks may be reduced, resulting in improved integrated circuit operating speeds.

Circuitry for low-precision deep learning

A method for designing a system on a target device includes identifying a length for a carry chain that is supported by predefined quanta of a resource on the target device. A plurality of logical adders is mapped onto a single logical adder implemented on the carry chain subject to the identified length to increase logic utilization in a design for the system.

Method and apparatus for performing field programmable gate array packing with continuous carry chains

A programmable device may be configured to support machine learning training operations using matrix multiplication circuitry implemented on a systolic array. The systolic array includes an array of processing elements, each of which includes hybrid floating-point dot-product circuitry. The hybrid dot-product circuitry has a hard data path that uses digital signal processing (DSP) blocks operating in floating-point mode and a hard/soft data path that uses DSP blocks operating in fixed-point mode operated in conjunction with general purpose soft logic. The hard/soft data path includes 2-element dot-product circuits that feed an adder tree. Results from the hard data path are combined with the adder tree using format conversion and normalization circuitry. Inputs to the hybrid dot-product circuitry may be in the BFLOAT16 format. The hard data path may be in the single precision format. The hard/soft data path uses a custom format that is similar to but different than BFLOAT16.

Machine learning training architecture for programmable devices

Multiplier circuitry includes first combinatorial circuitry configured to perform a combinatorial function, based at least in part on redundant form arithmetic, to generate a first subset of two or more partial products. The two or more partial products are based at least in part on a first input to the multiplier circuitry and a second input to the multiplier circuitry. The multiplier circuitry also includes a carry chain that includes a second combinatorial circuitry configured to generate a second subset of the two or more partial products based at least in part on the first input and the second input. Furthermore, the carry chain includes one or more binary ripple-carry adders configured to generate a product of the multiplier circuitry based at least in part on a sum of the two or more partial products.

Programmable-logic-directed multiplier mapping

A method for designing and configuring a system on a field programmable gate array (FPGA) is disclosed. A portion of the system that is implemented greater than a predetermined number of times is identified. A structural netlist that describes how to implement the portion of the system a plurality of times on the FPGA and that leverages a repetitive nature of implementing the portion is generated. The identifying and generating is performed prior to synthesizing and placing other portions of the system that are not implemented greater than the predetermined number of time. Synthesizing, placing, and routing the other portions of the system on the FPGA is performed in accordance with the structural netlist. The FPGA is configured with a configuration file that includes a design for the system that reflects the synthesizing, placing, and routing, wherein the configuring physically transforms resources on the FPGA to implement the system.

Method and apparatus for performing synthesis for field programmable gate array embedded feature placement

The present disclosure relates generally to techniques for enhancing packing density of carry-chains implemented on an integrated circuit. In particular, a packed-carry chain may be implemented to redistribute and/or emulate the logic of a first number of arithmetic logic cells of a first and/or second carry-chain using a second number of arithmetic logic cells less than or equal to the first number. By fitting the first and second carry-chain into such a packed carry-chain, the area consumed to perform the arithmetic operations of the first and second carry-chain may be reduced. As a result, the integrated circuit may benefit from increased efficiencies, reduced latency, and reduced resource consumption (e.g., wiring, area, and power).

Continuous carry-chain packing

Growing community of inventors

San Jose, CA, United States of America

Gregg William Baeckler