7,742 research outputs found
Challenges and Opportunities for RISC-V Architectures towards Genomics-based Workloads
The use of large-scale supercomputing architectures is a hard requirement for
scientific computing Big-Data applications. An example is genomics analytics,
where millions of data transformations and tests per patient need to be done to
find relevant clinical indicators. Therefore, to ensure open and broad access
to high-performance technologies, governments, and academia are pushing toward
the introduction of novel computing architectures in large-scale scientific
environments. This is the case of RISC-V, an open-source and royalty-free
instruction-set architecture. To evaluate such technologies, here we present
the Variant-Interaction Analytics use case benchmarking suite and datasets.
Through this use case, we search for possible genetic interactions using
computational and statistical methods, providing a representative case for
heavy ETL (Extract, Transform, Load) data processing. Current implementations
are implemented in x86-based supercomputers (e.g. MareNostrum-IV at the
Barcelona Supercomputing Center (BSC)), and future steps propose RISC-V as part
of the next MareNostrum generations. Here we describe the Variant Interaction
Use Case, highlighting the characteristics leveraging high-performance
computing, indicating the caveats and challenges towards the next RISC-V
developments and designs to come from a first comparison between x86 and RISC-V
architectures on real Variant Interaction executions over real hardware
implementations
Instruction Set Architectures for Quantum Processing Units
Progress in quantum computing hardware raises questions about how these
devices can be controlled, programmed, and integrated with existing
computational workflows. We briefly describe several prominent quantum
computational models, their associated quantum processing units (QPUs), and the
adoption of these devices as accelerators within high-performance computing
systems. Emphasizing the interface to the QPU, we analyze instruction set
architectures based on reduced and complex instruction sets, i.e., RISC and
CISC architectures. We clarify the role of conventional constraints on memory
addressing and instruction widths within the quantum computing context.
Finally, we examine existing quantum computing platforms, including the D-Wave
2000Q and IBM Quantum Experience, within the context of future ISA development
and HPC needs.Comment: To be published in the proceedings in the International Super
Computing Conference 2017 publicatio
Low Power Implementation of Non Power-of-Two FFTs on Coarse-Grain Reconfigurable Architectures
The DRM standard for digital radio broadcast in the AM band requires integrated devices for radio receivers at very low power. A System on Chip (SoC) call DiMITRI was developed based on a dual ARM9 RISC core architecture. Analyses showed that most computation power is used in the Coded Orthogonal Frequency Division Multiplexing (COFDM) demodulation to compute Fast Fourier Transforms (FFT) and inverse transforms (IFFT) on complex samples. These FFTs have to be computed on non power-of-two numbers of samples, which is very uncommon in the signal processing world. The results obtained with this chip, lead to the objective to decrease the power dissipated by the COFDM demodulation part using a coarse-grain reconfigurable structure as a coprocessor. This paper introduces two different coarse-grain architectures: PACT XPP technology and the Montium, developed by the University of Twente, and presents the implementation of a\ud
Fast Fourier Transform on 1920 complex samples. The implementation result on the Montium shows a saving of a factor 35 in terms of processing time, and 14 in terms of power consumption compared to the RISC implementation, and a\ud
smaller area. Then, as a conclusion, the paper presents the next steps of the development and some development issues
The development of iHARP: a multiple instruction issue processor chip
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