7,261 research outputs found
From FPGA to ASIC: A RISC-V processor experience
This work document a correct design flow using these tools in the Lagarto RISC- V Processor and the RTL design considerations that must be taken into account, to move from a design for FPGA to design for ASIC
BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations
Objective: The advent of High-Performance Computing (HPC) in recent years has
led to its increasing use in brain study through computational models. The
scale and complexity of such models are constantly increasing, leading to
challenging computational requirements. Even though modern HPC platforms can
often deal with such challenges, the vast diversity of the modeling field does
not permit for a single acceleration (or homogeneous) platform to effectively
address the complete array of modeling requirements. Approach: In this paper we
propose and build BrainFrame, a heterogeneous acceleration platform,
incorporating three distinct acceleration technologies, a Dataflow Engine, a
Xeon Phi and a GP-GPU. The PyNN framework is also integrated into the platform.
As a challenging proof of concept, we analyze the performance of BrainFrame on
different instances of a state-of-the-art neuron model, modeling the Inferior-
Olivary Nucleus using a biophysically-meaningful, extended Hodgkin-Huxley
representation. The model instances take into account not only the neuronal-
network dimensions but also different network-connectivity circumstances that
can drastically change application workload characteristics. Main results: The
synthetic approach of three HPC technologies demonstrated that BrainFrame is
better able to cope with the modeling diversity encountered. Our performance
analysis shows clearly that the model directly affect performance and all three
technologies are required to cope with all the model use cases.Comment: 16 pages, 18 figures, 5 table
Minimalistic SDHC-SPI hardware reader module for boot loader applications
This paper introduces a low-footprint full hardware boot loading solution for FPGA-based Programmable
Systems on Chip. The proposed module allows loading the system code and data from a standard SD card
without having to re-program the whole embedded system. The hardware boot loader is processor independent
and removes the need of a software boot loader and the related memory resources. The hardware overhead
introduced is manageable, even in low-range FPGA chips, and negligible in mid- and high-range devices. The
implementation of the SD card reader module is explained in detail and an example of a multi-boot loader is
offered as well. The multi-boot loader is implemented and tested with the Xilinx's Picoblaze microcontroller
PROGRAPE-1: A Programmable, Multi-Purpose Computer for Many-Body Simulations
We have developed PROGRAPE-1 (PROgrammable GRAPE-1), a programmable
multi-purpose computer for many-body simulations. The main difference between
PROGRAPE-1 and "traditional" GRAPE systems is that the former uses FPGA (Field
Programmable Gate Array) chips as the processing elements, while the latter
rely on the hardwired pipeline processor specialized to gravitational
interactions. Since the logic implemented in FPGA chips can be reconfigured, we
can use PROGRAPE-1 to calculate not only gravitational interactions but also
other forms of interactions such as van der Waals force, hydrodynamical
interactions in SPH calculation and so on. PROGRAPE-1 comprises two Altera
EPF10K100 FPGA chips, each of which contains nominally 100,000 gates. To
evaluate the programmability and performance of PROGRAPE-1, we implemented a
pipeline for gravitational interaction similar to that of GRAPE-3. One pipeline
fitted into a single FPGA chip, which operated at 16 MHz clock. Thus, for
gravitational interaction, PROGRAPE-1 provided the speed of 0.96
Gflops-equivalent. PROGRAPE will prove to be useful for wide-range of
particle-based simulations in which the calculation cost of interactions other
than gravity is high, such as the evaluation of SPH interactions.Comment: 20 pages with 9 figures; submitted to PAS
Memory and information processing in neuromorphic systems
A striking difference between brain-inspired neuromorphic processors and
current von Neumann processors architectures is the way in which memory and
processing is organized. As Information and Communication Technologies continue
to address the need for increased computational power through the increase of
cores within a digital processor, neuromorphic engineers and scientists can
complement this need by building processor architectures where memory is
distributed with the processing. In this paper we present a survey of
brain-inspired processor architectures that support models of cortical networks
and deep neural networks. These architectures range from serial clocked
implementations of multi-neuron systems to massively parallel asynchronous ones
and from purely digital systems to mixed analog/digital systems which implement
more biological-like models of neurons and synapses together with a suite of
adaptation and learning mechanisms analogous to the ones found in biological
nervous systems. We describe the advantages of the different approaches being
pursued and present the challenges that need to be addressed for building
artificial neural processing systems that can display the richness of behaviors
seen in biological systems.Comment: Submitted to Proceedings of IEEE, review of recently proposed
neuromorphic computing platforms and system
FPGA-Based Tracklet Approach to Level-1 Track Finding at CMS for the HL-LHC
During the High Luminosity LHC, the CMS detector will need charged particle
tracking at the hardware trigger level to maintain a manageable trigger rate
and achieve its physics goals. The tracklet approach is a track-finding
algorithm based on a road-search algorithm that has been implemented on
commercially available FPGA technology. The tracklet algorithm has achieved
high performance in track-finding and completes tracking within 3.4 s on a
Xilinx Virtex-7 FPGA. An overview of the algorithm and its implementation on an
FPGA is given, results are shown from a demonstrator test stand and system
performance studies are presented.Comment: Submitted to proceedings of Connecting The Dots/Intelligent Trackers
2017, Orsay, Franc
SpinLink: An interconnection system for the SpiNNaker biologically inspired multi-computer
SpiNNaker is a large-scale biologically-inspired multi-computer designed to model very heavily distributed problems, with the flagship application being the simulation of large neural networks. The project goal is to have one million processors included in a single machine, which consequently span many thousands of circuit boards. A computer of this scale imposes large communication requirements between these boards, and requires an extensible method of connecting to external equipment such as sensors, actuators and visualisation systems. This paper describes two systems that can address each of these problems.Firstly, SpinLink is a proposed method of connecting the SpiNNaker boards by using time-division multiplexing (TDM) to allow eight SpiNNaker links to run at maximum bandwidth between two boards. SpinLink will be deployed on Spartan-6 FPGAs and uses a locally generated clock that can be paused while the asynchronous links from SpiNNaker are sending data, thus ensuring a fast and glitch-free response. Secondly, SpiNNterceptor is a separate system, currently in the early stages of design, that will build upon SpinLink to address the important external I/O issues faced by SpiNNaker. Specifically, spare resources in the FPGAs will be used to implement the debugging and I/O interfacing features of SpiNNterceptor
GRAPE-6: The massively-parallel special-purpose computer for astrophysical particle simulation
In this paper, we describe the architecture and performance of the GRAPE-6
system, a massively-parallel special-purpose computer for astrophysical
-body simulations. GRAPE-6 is the successor of GRAPE-4, which was completed
in 1995 and achieved the theoretical peak speed of 1.08 Tflops. As was the case
with GRAPE-4, the primary application of GRAPE-6 is simulation of collisional
systems, though it can be used for collisionless systems. The main differences
between GRAPE-4 and GRAPE-6 are (a) The processor chip of GRAPE-6 integrates 6
force-calculation pipelines, compared to one pipeline of GRAPE-4 (which needed
3 clock cycles to calculate one interaction), (b) the clock speed is increased
from 32 to 90 MHz, and (c) the total number of processor chips is increased
from 1728 to 2048. These improvements resulted in the peak speed of 64 Tflops.
We also discuss the design of the successor of GRAPE-6.Comment: Accepted for publication in PASJ, scheduled to appear in Vol. 55, No.
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