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At least 37 records · Page 2

Fast jet tagging with MLP-Mixers on FPGAs

We explore the innovative use of MLP-Mixer models for real-time jet tagging and establish their feasibility on resource-constrained hardware like FPGAs. MLP-Mixers excel in processing sequences of jet constituents, achieving state-of-the-art performance on datasets mimicking Large Hadron Collider conditions. By using advanced optimization techniques such as High-Granularity Quantization and Distributed Arithmetic, we achieve unprecedented efficiency. These models match or surpass the accuracy of previous architectures, reduce hardware resource usage by up to 97%, double the throughput, and half the latency. Additionally, non-permutation-invariant architectures enable smart feature prioritization and efficient FPGA deployment, setting a new benchmark for machine learning in real-time data processing at particle colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Analyzing the effectiveness of a frame-level redundancy scrubbing technique for SRAM-based FPGAs

Radiation effects such as soft errors are the major threat to the reliability of SRAM-based FPGAs. This work analyzes the effectiveness in correcting soft errors of a novel scrubbing technique using internal frame redundancy called Frame-level Redundancy Scrubbing (FLR-scrubbing). This correction technique can be implemented in a coarse grain TMR design. The FLR-scrubbing technique was implemented on a mid-size Xilinx Virtex-5 FPGA device used as a case study. The FLR-scrubbing technique was tested under neutron radiation and fault injection. Implementation results demonstrated minimum area and energy consumption overhead when compared to other techniques. The time to repair the fault is also improved by using the Internal Configuration Access Port (ICAP). Lastly, neutron radiation test results demonstrated that the proposed technique is suitable for correcting accumulated SEUs and MBUs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

FPGAs as a Service to Accelerate Machine Learning Inference [PowerPoint]

Large-scale particle physics experiments face challenging demands for high-throughput computing resources both now and in the future. New heterogeneous computing paradigms on dedicated hardware with increased parallelization, such as Field Programmable Gate Arrays (FPGAs), offer exciting solutions with large potential gains. The growing applications of machine learning algorithms in particle physics for simulation, reconstruction, and analysis are naturally deployed on such platforms. We demonstrate that the acceleration of machine learning inference as a web service represents a heterogeneous computing solution for particle physics experiments that requires minimal modification to the current computing model. As examples, we retrain the ResNet-50 convolutional neural network to demonstrate state-of-the-art performance for top quark jet tagging at the LHC, and apply a ResNet-50 model with transfer learning for neutrino event classification. Using Project Brainwave b y Microsoft to accelerate the ResNet-50 image classification model, we achieve average inference times of 60 (10) milliseconds with our experimental physics software framework using Brainwave as a cloud (edge or on-premises) service, representing an improvement by a factor of approximately 30 (175) in model inference latency over traditional CPU inference in current experimental hardware. A single FPGA service accessed by many CPUs achieves a throughput of 600--700 inferences per second using an image batch of one, comparable to large batch-size GPU throughput and significantly better than small batch-size GPU throughput. Deployed as an edge or cloud service for the particle physics computing model, coprocessor accelerators can have a higher duty cycle and are potentially much more cost-effective.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Deploying Simulations to FPGAs for HIL-Style Tester Development

Hardware-in-the-Loop (HIL) methodologies for test system development often require simulations capable of running at MHz speeds on FPGAs. The stringent memory and speed constraints necessitate compromises between model fidelity and execution speed. Numerically solving the underlying governing equations represents the highest accuracy, but slowest responding approach. By storing pre-determined results in look-up-tables (LUT), one can balance speed and accuracy.

97 MATHEMATICS AND COMPUTING↗

HGQ: High Granularity Quantization for Real-time Neural Networks on FPGAs

Neural networks with sub-microsecond inference latency are required by many critical applications. Targeting such applications deployed on FPGAs, we present High Granularity Quantization (HGQ), a quantization-aware training framework that optimizes parameter bit-widths through gradient descent. Unlike conventional methods, HGQ determines the optimal bit-width for each parameter independently, making it suitable for hardware platforms supporting heterogeneous arbitrary precision arithmetic. In our experiments, HGQ shows superior performance compared to existing network compression methods, achieving orders of magnitude reduction in resource consumption and latency while maintaining the accuracy on several benchmark tasks. These improvements enable the deployment of complex models previously infeasible due to resource or latency constraints. HGQ is open-source and is used for developing next-generation trigger systems at the CERN ATLAS and CMS experiments for particle physics, enabling the use of advanced machine learning models for real-time data selection with sub-microsecond latency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Genetic Representation for Evolutionary Fault Recovery in Virtex FPGAs

Most evolutionary approaches to fault recovery in FPGAs focus on evolving alternative logic configurations as opposed to evolving the intra-cell routing. Since the majority of transistors in a typical FPGA are dedicated to interconnect, nearly 80% according to one estimate, evolutionary fault-recovery systems should benefit hy accommodating routing. In this paper, we propose an evolutionary fault-recovery system employing a genetic representation that takes into account both logic and routing configurations. Experiments were run using a software model of the Xilinx Virtex FPGA. We report that using four Virtex combinational logic blocks, we were able to evolve a 100% accurate quadrature decoder finite state machine in the presence of a stuck-at-zero fault.

Lohn, Jason↗

Operation of FPGAs at Extremely Low Temperatures

This paper describes the operation of FPGAs at very low temperatures eg -160(deg)C. Both Actel and Xilinx parts are tested It was found that low temperature operations is not a problem with the parts tested, but there is a problem with powering on an FPGA at cold temperatures.

Field-Programmable Gate Array (FPGA)↗

Replication of Space-Shuttle Computers in FPGAs and ASICs

A document discusses the replication of the functionality of the onboard space-shuttle general-purpose computers (GPCs) in field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs). The purpose of the replication effort is to enable utilization of proven space-shuttle flight software and software-development facilities to the extent possible during development of software for flight computers for a new generation of launch vehicles derived from the space shuttles. The replication involves specifying the instruction set of the central processing unit and the input/output processor (IOP) of the space-shuttle GPC in a hardware description language (HDL). The HDL is synthesized to form a "core" processor in an FPGA or, less preferably, in an ASIC. The core processor can be used to create a flight-control card to be inserted into a new avionics computer. The IOP of the GPC as implemented in the core processor could be designed to support data-bus protocols other than that of a multiplexer interface adapter (MIA) used in the space shuttle. Hence, a computer containing the core processor could be tailored to communicate via the space-shuttle GPC bus and/or one or more other buses.

Ferguson, Roscoe C.↗

Mitigating Upsets in SRAM-Based FPGAs from the Xilinx Virtex 2 Family

Static random access memory (SRAM) upset rates in field programmable gate arrays (FPGAs) from the Xilinx Virtex 2 family have been tested for radiation effects on configuration memory, block RAM and the power-on-reset (POR) and SelectMAP single event functional interrupts (SEFIs). Dynamic testing has shown the effectiveness and value of Triple Module Redundancy (TMR) and partial reconfiguration when used in conjunction. Continuing dynamic testing for more complex designs and other Virtex 2 capabilities (i.e., I/O standards, digital clock managers (DCM), etc.) is scheduled.

SEE testing↗

Board Saver for Use with Developmental FPGAs

A device denoted a board saver has been developed as a means of reducing wear and tear of a printed-circuit board onto which an antifuse field programmable gate array (FPGA) is to be eventually soldered permanently after a number of design iterations. The need for the board saver or a similar device arises because (1) antifuse-FPGA design iterations are common and (2) repeated soldering and unsoldering of FPGAs on the printed-circuit board to accommodate design iterations can wear out the printed-circuit board. The board saver is basically a solderable/unsolderable FPGA receptacle that is installed temporarily on the printed-circuit board. The board saver is, more specifically, a smaller, square-ring-shaped, printed-circuit board (see figure) that contains half via holes one for each contact pad along its periphery. As initially fabricated, the board saver is a wider ring containing full via holes, but then it is milled along its outer edges, cutting the via holes in half and laterally exposing their interiors. The board saver is positioned in registration with the designated FPGA footprint and each via hole is soldered to the outer portion of the corresponding FPGA contact pad on the first-mentioned printed-circuit board. The via-hole/contact joints can be inspected visually and can be easily unsoldered later. The square hole in the middle of the board saver is sized to accommodate the FPGA, and the thickness of the board saver is the same as that of the FPGA. Hence, when a non-final FPGA is placed in the square hole, the combination of the non-final FPGA and the board saver occupy no more area and thickness than would a final FPGA soldered directly into its designated position on the first-mentioned circuit board. The contact leads of a non-final FPGA are not bent and are soldered, at the top of the board saver, to the corresponding via holes. A non-final FPGA can readily be unsoldered from the board saver and replaced by another one. Once the final FPGA design has been determined, the board saver can be unsoldered from the contact pads on the first-mentioned printed-circuit board and replaced by the final FPGA.

Berkun, Andrew↗

Impact of Negative Bias Temperature Instability on FPGAs

In this sliide presentation the statistical impact of PMOS Negative Bias Temperature Instability (NBTI) degradation on circuit delay is reviewed. An on-board timing circuitry that was been developed to detect and measure timing delays in SRAM-based LUT commercial FPGAs is described. The initial experimental data on the on-board timing circuit are reviewed.

pixel reliability↗

Reconfigurable Fault Tolerance for FPGAs

The invention allows a field-programmable gate array (FPGA) or similar device to be efficiently reconfigured in whole or in part to provide higher capacity, non-redundant operation. The redundant device consists of functional units such as adders or multipliers, configuration memory for the functional units, a programmable routing method, configuration memory for the routing method, and various other features such as block RAM, I/O (random access memory, input/output) capability, dedicated carry logic, etc. The redundant device has three identical sets of functional units and routing resources and majority voters that correct errors. The configuration memory may or may not be redundant, depending on need. For example, SRAM-based FPGAs will need some type of radiation-tolerant configuration memory, or they will need triple-redundant configuration memory. Flash or anti-fuse devices will generally not need redundant configuration memory. Some means of loading and verifying the configuration memory is also required. These are all components of the pre-existing redundant FPGA. This innovation modifies the voter to accept a MODE input, which specifies whether ordinary voting is to occur, or if redundancy is to be split. Generally, additional routing resources will also be required to pass data between sections of the device created by splitting the redundancy. In redundancy mode, the voters produce an output corresponding to the two inputs that agree, in the usual fashion. In the split mode, the voters select just one input and convey this to the output, ignoring the other inputs. In a dual-redundant system (as opposed to triple-redundant), instead of a voter, there is some means to latch or gate a state update only when both inputs agree. In this case, the invention would require modification of the latch or gate so that it would operate normally in redundant mode, and would separately latch or gate the inputs in non-redundant mode.

Shuler, Robert, Jr.↗

Digital Radar-Signal Processors Implemented in FPGAs

High-performance digital electronic circuits for onboard processing of return signals in an airborne precipitation- measuring radar system have been implemented in commercially available field-programmable gate arrays (FPGAs). Previously, it was standard practice to downlink the radar-return data to a ground station for postprocessing a costly practice that prevents the nearly-real-time use of the data for automated targeting. In principle, the onboard processing could be performed by a system of about 20 personal- computer-type microprocessors; relative to such a system, the present FPGA-based processor is much smaller and consumes much less power. Alternatively, the onboard processing could be performed by an application-specific integrated circuit (ASIC), but in comparison with an ASIC implementation, the present FPGA implementation offers the advantages of (1) greater flexibility for research applications like the present one and (2) lower cost in the small production volumes typical of research applications. The generation and processing of signals in the airborne precipitation measuring radar system in question involves the following especially notable steps: The system utilizes a total of four channels two carrier frequencies and two polarizations at each frequency. The system uses pulse compression: that is, the transmitted pulse is spread out in time and the received echo of the pulse is processed with a matched filter to despread it. The return signal is band-limited and digitally demodulated to a complex baseband signal that, for each pulse, comprises a large number of samples. Each complex pair of samples (denoted a range gate in radar terminology) is associated with a numerical index that corresponds to a specific time offset from the beginning of the radar pulse, so that each such pair represents the energy reflected from a specific range. This energy and the average echo power are computed. The phase of each range bin is compared to the previous echo by complex conjugate multiplication to obtain the mean Doppler shift (and hence the mean and variance of the velocity of precipitation) of the echo at that range.

Berkun, Andrew↗

Radiation Hardening by Software Techniques on FPGAs: Flight Experiment Evaluation and Results

We present our work on implementing Radiation Hardening by Software (RHBSW) techniques on the Xilinx Virtex5 FPGAs PowerPC 440 processors on the SpaceCube 2.0 platform. The techniques have been matured and tested through simulation modeling, fault emulation, laser fault injection and now in a flight experiment, as part of the Space Test Program- Houston 4-ISS SpaceCube Experiment 2.0 (STP-H4-ISE 2.0). This work leverages concepts such as heartbeat monitoring, control flow assertions, and checkpointing, commonly used in the High Performance Computing industry, and adapts them for use in remote sensing embedded systems. These techniques are extremely low overhead (typically <1.3%), enabling a 3.3x gain in processing performance as compared to the equivalent traditionally radiation hardened processor. The recently concluded STP-H4 flight experiment was an opportunity to upgrade the RHBSW techniques for the Virtex5 FPGA and demonstrate them on-board the ISS to achieve TRL 7. This work details the implementation of the RHBSW techniques, that were previously developed for the Virtex4-based SpaceCube 1.0 platform, on the Virtex5-based SpaceCube 2.0 flight platform. The evaluation spans the development and integration with flight software, remotely uploading the new experiment to the ISS SpaceCube 2.0 platform, and conducting the experiment continuously for 16 days before the platform was decommissioned. The experiment was conducted on two PowerPCs embedded within the Virtex5 FPGA devices and the experiment collected 19,400 checkpoints, processed 253,482 status messages, and incurred 0 faults. These results are highly encouraging and future work is looking into longer duration testing as part of the STP-H5 flight experiment.

Hybrid Flight Architectures↗

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning

Although Transformer-based language representations achieve state-of-the-art accuracy on various natural language processing (NLP) tasks, the large model size has been challenging the resource constrained computing platforms. Weight pruning, as a popular and effective technique in reducing the number of weight parameters and accelerating the Transformer, has been investigated on GPUs. However, the Transformer acceleration using weight pruning on field-programmable gate array (FPGAs) remains unexplored. This paper investigates the column balanced block-wise pruning on Transformer and designs an FPGA acceleration engine to customize the balanced blockwise matrix multiplication. We implement the Transformer model with proper hardware scheduling, and the experiments show that the Transformer inference on FPGA achieves 10.35 ms latency with the batch size of 32, which is 10.96 × speed up comparing to CPU platform and 2.08 × speed up comparing to GPU platform.

Peng, Hongwu↗

Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider

In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely challenging environment of a real-time event selection system at the Large Hadron Collider (LHC). We demonstrate that new physics signatures can be enhanced by three orders of magnitude, while staying within the strict latency and resource constraints of a typical LHC event filtering system. This would allow for collecting datasets potentially enriched with high-purity contributions from new physics processes. Through per-layer, highly parallel implementations of network layers, support for autoencoder-specific losses on FPGAs and latent space based inference, we demonstrate that anomaly detection can be performed in as little as $80\,$ns using less than 3% of the logic resources in the Xilinx Virtex VU9P FPGA. Opening the way to real-life applications of this idea during the next data-taking campaign of the LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗