| 1. |
- Huyghe, Jeroen R., et al.
(author)
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Discovery of common and rare genetic risk variants for colorectal cancer
- 2019
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:1, s. 76-
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Journal article (peer-reviewed)abstract
- To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 x 10(-8), bringing the number of known independent signals for CRC to similar to 100. New signals implicate lower-frequency variants, Kruppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.
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| 2. |
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| 3. |
- Liu, Ming, et al.
(author)
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A High-End Reconfigurable Computation Platform for Nuclear and Particle Physics Experiments
- 2011
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In: Computing in science & engineering (Print). - 1521-9615 .- 1558-366X. ; 13:2, s. 52-63
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Journal article (peer-reviewed)abstract
- A high-performance computation platform based on field-programmable gate arrays targets nuclear and particle physics experiment applications. The system can be constructed or scaled into a supercomputer-equivalent size for detector data processing by inserting compute nodes into advanced telecommunications computing architecture (ATCA) crates. Among the case study results are that one ATCA crate can provide a computation capability equivalent to hundreds of commodity PCs for Hades online particle track reconstruction and Cherenkov ring recognition.
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| 4. |
- Liu, Ming, 1982-
(author)
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A High-end Reconfigurable Computation Platform for Particle Physics Experiments
- 2008
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Licentiate thesis (other academic/artistic)abstract
- Modern nuclear and particle physics experiments run at a very high reaction rate and are able to deliver a data rate of up to hundred GBytes/s. This data rate is far beyond the storage and on-line analysis capability. Fortunately physicists have only interest in a very small proportion among the huge amounts of data. Therefore in order to select the interesting data and reject the background by sophisticated pattern recognition processing, it is essential to realize an efficient data acquisition and trigger system which results in a reduced data rate by several orders of magnitude. Motivated by the requirements from multiple experiment applications, we are developing a high-end reconfigurable computation platform for data acquisition and triggering. The system consists of a scalable number of compute nodes, which are fully interconnected by high-speed communication channels. Each compute node features 5 Xilinx Virtex-4 FX60 FPGAs and up to 10 GBytesDDR2 memory. A hardware/software co-design approach is proposed to develop custom applications on the platform, partitioning performance-critical calculation to the FPGA hardware fabric while leaving flexible and slow controls to the embedded CPU plus the operating system. The system is expected to be high-performance and general-purpose for various applications especially in the physics experiment domain. As a case study, the particle track reconstruction algorithm for HADES has been developed and implemented on the computation platform in the format of processing engines. The Tracking Processing Unit (TPU) recognizes peak bins on the projection plane and reconstructs particle tracks in realtime. Implementation results demonstrate its acceptable resource utilization and the feasibility to implement the module together with the sys-tem design on the FPGA. Experimental results show that the online track reconstruction computation achieves 10.8 - 24.3 times performance acceleration per TPU module when compared to the software solution on a Xeon2.4 GHz commodity server.
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| 5. |
- Liu, Ming, et al.
(author)
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A Reconfigurable Design Framework for FPGA Adaptive Computing
- 2009
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In: 2009 INTERNATIONAL CONFERENCE ON RECONFIGURABLE COMPUTING AND FPGAS. - : IEEE. - 9781424452934 ; , s. 439-444
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Conference paper (peer-reviewed)abstract
- Partial Reconfiguration (PR) offers the possibility to adaptively change part of the FPGA design without stopping the remaining system. In this paper, we present a comprehensive framework for adaptive computing, in which design key points of hardware processes, system interconnections, Operating Systems (OS), device drivers, scheduler software as well as context switching are respectively concerned in different hardware/software layers. A case study is discussed to demonstrate an example of swapping a Flash memory controller and an SRAM controller in response to diverse memory access needs. Result analysis reveals a more efficient resource utilization of 52.1% I/O pads, 86.5% LUTs and 81.3% Flip-Flops, when compared to the static design with same functionalities. A small reconfiguration overhead of context switching is measured within the range from hundreds of microseconds to milliseconds. Moreover, technical perspectives are analyzed and it is foreseen to obtain great benefits with the proposed design framework in object applications of particle physics experiments.
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| 6. |
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| 7. |
- Liu, Ming, et al.
(author)
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ATCA-based Computation Platform for Data Acquisition and Triggering in Particle Physics Experiments
- 2008
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In: 2008 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE AND LOGIC APPLICATIONS, VOLS 1 AND 2. ; , s. 287-292
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Conference paper (peer-reviewed)abstract
- An ATCA-based computation platform for data acquisition and trigger applications in nuclear and particle physics experiments has been developed. Each Compute Node (CN) which appears as a Field Replaceable Unit (FRU) in an ATCA shelf, features 5 Xilinx Virtex-4 FX60 FPGAs and up to 10 GBytes DDR2 memory. Connectivity is provided with 8 optical links and 5 Gigabit Ethernet ports, which are mounted on each board to receive data from detectors and forward results to outer shelves or PC farms with attached mass storage. Fast point-to-point on-board interconnections between FPGAs as well as the full-mesh shelf backplane provide flexibility and high bandwidth to partition algorithms and correlate results among them. The system represents a highly reconfigurable and scalable solution for multiple applications.
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| 8. |
- Liu, Ming, et al.
(author)
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FPGA-based adaptive computing for correlated multi-stream processing
- 2010
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In: Proceedings -Design, Automation and Test in Europe, DATE. - : IEEE Computer Society. - 9783981080162 ; , s. 973-976
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Conference paper (peer-reviewed)abstract
- In conventional static implementations for correlated streaming applications, computing resources may be inefficiently utilized since multiple stream processors may supply their sub-results at asynchronous rates for result correlation or synchronization. To enhance the resource utilization efficiency, we analyze multi-streaming models and implement an adaptive architecture based on FPGA Partial Reconfiguration (PR) technology. The adaptive system can intelligently schedule and manage various processing modules during run-time. Experimental results demonstrate up to 78.2% improvement in throughput-per-unit- area on unbalanced processing of correlated streams, as well as only 0.3% context switching overhead in the overall processing time in the worst-case.
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| 9. |
- Liu, Ming, et al.
(author)
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FPGA-based Cherenkov Ring Recognition in Nuclear and Particle Physics Experiments
- 2011
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In: Reconfigurable Computing. - Berlin, Heidelberg : Springer. - 9783642194740 ; , s. 169-180
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Conference paper (peer-reviewed)abstract
- Cherenkov ring is often adopted to identify particles flying through the detector systems in nuclear and particle physics experiments. In this paper, we introduce an improved ring recognition algorithm and present its FPGA implementation. Compared to the previous implementation based on VMEBus and FPGAs, our design is evaluated to outperform by several tens up to hundred times with acceptable resource utilizations on a Xilinx Virtex-4 FX60 FPGA. The design module will reside in the online data acquisition (DAQ) and trigger facilities, and contribute to significantly reduce the data rate of storage for offline analysis by retaining only interesting events and dropping the noise. Our customized FPGA cluster in one ATCA [1] shelf is foreseen to achieve an equivalent computation capability up to thousands of commodity PCs for particle recognition.
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