848 research outputs found
Towards Lattice Quantum Chromodynamics on FPGA devices
In this paper we describe a single-node, double precision Field Programmable
Gate Array (FPGA) implementation of the Conjugate Gradient algorithm in the
context of Lattice Quantum Chromodynamics. As a benchmark of our proposal we
invert numerically the Dirac-Wilson operator on a 4-dimensional grid on three
Xilinx hardware solutions: Zynq Ultrascale+ evaluation board, the Alveo U250
accelerator and the largest device available on the market, the VU13P device.
In our implementation we separate software/hardware parts in such a way that
the entire multiplication by the Dirac operator is performed in hardware, and
the rest of the algorithm runs on the host. We find out that the FPGA
implementation can offer a performance comparable with that obtained using
current CPU or Intel's many core Xeon Phi accelerators. A possible multiple
node FPGA-based system is discussed and we argue that power-efficient High
Performance Computing (HPC) systems can be implemented using FPGA devices only.Comment: 17 pages, 4 figure
Application-Specific Number Representation
Reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs), enable application-
specific number representations. Well-known number formats include fixed-point, floating-
point, logarithmic number system (LNS), and residue number system (RNS). Such different
number representations lead to different arithmetic designs and error behaviours, thus produc-
ing implementations with different performance, accuracy, and cost.
To investigate the design options in number representations, the first part of this thesis presents
a platform that enables automated exploration of the number representation design space. The
second part of the thesis shows case studies that optimise the designs for area, latency or
throughput from the perspective of number representations.
Automated design space exploration in the first part addresses the following two major issues:
² Automation requires arithmetic unit generation. This thesis provides optimised
arithmetic library generators for logarithmic and residue arithmetic units, which support
a wide range of bit widths and achieve significant improvement over previous designs.
² Generation of arithmetic units requires specifying the bit widths for each
variable. This thesis describes an automatic bit-width optimisation tool called R-Tool,
which combines dynamic and static analysis methods, and supports different number
systems (fixed-point, floating-point, and LNS numbers).
Putting it all together, the second part explores the effects of application-specific number
representation on practical benchmarks, such as radiative Monte Carlo simulation, and seismic
imaging computations. Experimental results show that customising the number representations
brings benefits to hardware implementations: by selecting a more appropriate number format,
we can reduce the area cost by up to 73.5% and improve the throughput by 14.2% to 34.1%; by
performing the bit-width optimisation, we can further reduce the area cost by 9.7% to 17.3%.
On the performance side, hardware implementations with customised number formats achieve
5 to potentially over 40 times speedup over software implementations
State-of-the-art in Smith-Waterman Protein Database Search on HPC Platforms
Searching biological sequence database is a common and repeated task in bioinformatics and molecular biology. The Smith–Waterman algorithm is the most accurate method for this kind of search. Unfortunately, this algorithm is computationally demanding and the situation gets worse due to the exponential growth of biological data in the last years. For that reason, the scientific community has made great efforts to accelerate Smith–Waterman biological database searches in a wide variety of hardware platforms. We give a survey of the state-of-the-art in Smith–Waterman protein database search, focusing on four hardware architectures: central processing units, graphics processing units, field programmable gate arrays and Xeon Phi coprocessors. After briefly describing each hardware platform, we analyse temporal evolution, contributions, limitations and experimental work and the results of each implementation. Additionally, as energy efficiency is becoming more important every day, we also survey performance/power consumption works. Finally, we give our view on the future of Smith–Waterman protein searches considering next generations of hardware architectures and its upcoming technologies.Instituto de Investigación en InformáticaUniversidad Complutense de Madri
OSWALD: OpenCL Smith–Waterman on Altera’s FPGA for Large Protein Databases
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. Unfortunately, the Smith–Waterman algorithm has quadratic time complexity, which makes it computationally demanding for large protein databases. In this paper, we present OSWALD, a portable, fully functional and general implementation to accelerate Smith–Waterman database searches in heterogeneous platforms based on Altera’s FPGA. OSWALD exploits OpenMP multithreading and SIMD computing through SSE and AVX2 extensions on the host while taking advantage of pipeline and vectorial parallelism by way of OpenCL on the FPGAs. Performance evaluations on two different heterogeneous architectures with real amino acid datasets show that OSWALD is competitive in comparison with other top-performing Smith–Waterman implementations, attaining up to 442 GCUPS peak with the best GCUPS/watts ratio.First published June 30, 2016. Article available in: Vol. 32, Issue 3, 2018.Facultad de Informátic
OSWALD: OpenCL Smith–Waterman on Altera’s FPGA for Large Protein Databases
The well-known Smith–Waterman algorithm is a high-sensitivity method for local sequence alignment. Unfortunately, the Smith–Waterman algorithm has quadratic time complexity, which makes it computationally demanding for large protein databases. In this paper, we present OSWALD, a portable, fully functional and general implementation to accelerate Smith–Waterman database searches in heterogeneous platforms based on Altera’s FPGA. OSWALD exploits OpenMP multithreading and SIMD computing through SSE and AVX2 extensions on the host while taking advantage of pipeline and vectorial parallelism by way of OpenCL on the FPGAs. Performance evaluations on two different heterogeneous architectures with real amino acid datasets show that OSWALD is competitive in comparison with other top-performing Smith–Waterman implementations, attaining up to 442 GCUPS peak with the best GCUPS/watts ratio.First published June 30, 2016. Article available in: Vol. 32, Issue 3, 2018.Facultad de Informátic
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