| 1. |
- Bott, Lukas Thomas, et al.
(författare)
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Coulomb dissociation of O-16 into He-4 and C-12
- 2023
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Ingår i: NUCLEAR PHYSICS IN ASTROPHYSICS - X, NPA-X 2022. - : EDP Sciences. - 2100-014X. ; 279
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Konferensbidrag (refereegranskat)abstract
- We measured the Coulomb dissociation of O-16 into He-4 and C-12 within the FAIR Phase-0 program at GSI Helmholtzzentrum fur Schwerionenforschung Darmstadt, Germany. From this we will extract the photon dissociation cross section O-16(alpha,gamma)C-12, which is the time reversed reaction to C-12(alpha,gamma)O-16. With this indirect method, we aim to improve on the accuracy of the experimental data at lower energies than measured so far. The expected low cross section for the Coulomb dissociation reaction and close magnetic rigidity of beam and fragments demand a high precision measurement. Hence, new detector systems were built and radical changes to the (RB)-B-3 setup were necessary to cope with the high-intensity O-16 beam. All tracking detectors were designed to let the unreacted O-16 ions pass, while detecting the C-12 and He-4.
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| 2. |
- Castañeda Lozano, Roberto, 1986-
(författare)
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Constraint-Based Register Allocation and Instruction Scheduling
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to improve latency or throughput) are central compiler problems. This dissertation proposes a combinatorial optimization approach to these problems that delivers optimal solutions according to a model, captures trade-offs between conflicting decisions, accommodates processor-specific features, and handles different optimization criteria.The use of constraint programming and a novel program representation enables a compact model of register allocation and instruction scheduling. The model captures the complete set of global register allocation subproblems (spilling, assignment, live range splitting, coalescing, load-store optimization, multi-allocation, register packing, and rematerialization) as well as additional subproblems that handle processor-specific features beyond the usual scope of conventional compilers.The approach is implemented in Unison, an open-source tool used in industry and research that complements the state-of-the-art LLVM compiler. Unison applies general and problem-specific constraint solving methods to scale to medium-sized functions, solving functions of up to 647 instructions optimally and improving functions of up to 874 instructions. The approach is evaluated experimentally using different processors (Hexagon, ARM and MIPS), benchmark suites (MediaBench and SPEC CPU2006), and optimization criteria (speed and code size reduction). The results show that Unison generates code of slightly to significantly better quality than LLVM, depending on the characteristics of the targeted processor (1% to 9.3% mean estimated speedup; 0.8% to 3.9% mean code size reduction). Additional experiments for Hexagon show that its estimated speedup has a strong monotonic relationship to the actual execution speedup, resulting in a mean speedup of 5.4% across MediaBench applications.The approach contributed by this dissertation is the first of its kind that is practical (it captures the complete set of subproblems, scales to medium-sized functions, and generates executable code) and effective (it generates better code than the LLVM compiler, fulfilling the promise of combinatorial optimization). It can be applied to trade compilation time for code quality beyond the usual optimization levels, explore and exploit processor-specific features, and identify improvement opportunities in conventional compilers.
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| 3. |
- Castañeda Lozano, Roberto, 1986-, et al.
(författare)
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Constraint-based register allocation and instruction scheduling
- 2012
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642335570 - 9783642335587 ; , s. 750-766
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Konferensbidrag (refereegranskat)abstract
- This paper introduces a constraint model and solving techniques for code generation in a compiler back-end. It contributes a new model for global register allocation that combines several advanced aspects: multiple register banks (subsuming spilling to memory), coalescing, and packing. The model is extended to include instruction scheduling and bundling. The paper introduces a decomposition scheme exploiting the underlying program structure and exhibiting robust behavior for functions with thousands of instructions. Evaluation shows that code quality is on par with LLVM, a state-of-the-art compiler infrastructure. The paper makes important contributions to the applicability of constraint programming as well as compiler construction: essential concepts are unified in a high-level model that can be solved by readily available modern solvers. This is a significant step towards basing code generation entirely on a high-level model and by this facilitates the construction of correct, simple, flexible, robust, and high-quality code generators.
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| 4. |
- Castañeda Lozano, Roberto, 1986-, et al.
(författare)
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Survey on Combinatorial Register Allocation and Instruction Scheduling
- 2018
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Ingår i: ACM Computing Surveys. - : ACM Press. - 0360-0300 .- 1557-7341.
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Tidskriftsartikel (refereegranskat)abstract
- Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time.This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization.
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| 5. |
- Castañeda Lozano, Roberto, et al.
(författare)
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Testing Continuous Double Auctions with a Constraint-Based Oracle
- 2010
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Ingår i: PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING-CP 2010. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642153952 ; , s. 613-627
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Konferensbidrag (refereegranskat)abstract
- Computer trading systems are essential for today's financial markets where the trading systems' correctness is of paramount economical significance. Automated random testing is a useful technique to find bugs in these systems, but it requires an independent system to decide the correctness of the system under test (known as oracle problem). This paper introduces a constraint-based oracle for random testing of a real-world trading system. The oracle provides the expected results by generating and solving constraint models of the trading system's continuous double auction. Constraint programming is essential for the correctness of the test oracle as the logic for calculating trades can be mapped directly to constraint models. The paper shows that the generated constraint models can be solved efficiently. Most importantly, the approach is shown to be successful by finding errors in a deployed financial trading system and in its specification.
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| 6. |
- Corcoran, Diarmuid, et al.
(författare)
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Efficient Real-Time Traffic Generation for 5G RAN
- 2020
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Ingår i: Proceedings of IEEE/IFIP Network Operations and Management Symposium 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728149738
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Konferensbidrag (refereegranskat)abstract
- Modern telecommunication and mobile networks are increasingly complex from a resource management perspective, with diverse combinations of software and infrastructure elements that need to be configured and tuned for efficient operation with high quality of service. Increased real-time automation at all levels and time-frames is a critical tool in controlling this complexity. A key component in automation is practical and accurate simulation methods that can be used in live traffic scenarios. This paper introduces a new method with supporting algorithms for sampling key parameters from live or recorded traffic which can be used to generate large volumes of synthetic traffic with very similar rate distributions and temporal characteristics. Multiple spatial renewal processes are used to generate fractional Gaussian noise, which is scaled and transformed into a log-normal rate distribution with discrete arrival events, fitted to the properties observed in given recorded traces. This approach works well for modelling large user aggregates but is especially useful for medium sized and relatively small aggregates, where existing methods struggle to reproduce the most important properties of recorded traces. The technique is demonstrated through experimental comparisons with data collected from an operational LTE network to be highly useful in supporting self-learning and automation algorithms which can ultimately reduce complexity, increase energy efficiency, and reduce total network operation costs.
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| 7. |
- Delgado, Alberto, et al.
(författare)
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Generating Optimal Stowage Plans for Container Vessel Bays
- 2009
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Ingår i: PRINCIPLES AND PRACTICE OF CONSTRAINT PROGRAMMING. - Berlin, Heidelberg : Springer Berlin Heidelberg. ; , s. 6-20
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Konferensbidrag (refereegranskat)abstract
- Millions of containers are stowed ever.), week with goods worth billions of dollars, but container vessel stowage is an all but neglected combinatorial optimization problem. In this paper, we introduce a model for stowing containers in a vessel bay which is the result of probably the longest collaboration to date with a liner shipping company on automated stowage planning. We then show how to solve this model efficiently in - to our knowledge - the first; application of CP to stowage planning using state-of-the-art techniques such as extensive use of global constraints, viewpoints, static and dynamic symmetry breaking, decomposed branching strategies, and early failure detection. Our CP approach outperforms an integer programming and column generation approach in a preliminary study. Since a complete model of this problem includes even more logical constraints, we believe that stowage planning is a new application area, for CP with a high impact potential.
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| 8. |
- Farshin, Alireza, 1992-, et al.
(författare)
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Scheduling - A Secret Sauce For Resource Disaggregation
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- This technical report describes the design & implementation of a constraint-based framework for scheduling & resource allocation in a disaggregated data center (DDC) where we build logical servers from disaggregated resources. We show that an Service LevelObjective (SLO)-aware constraint-based solver could improve a data center’s resource utilization by finding better solutions based on provided workload characteristics.
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| 9. |
- Flener, Pierre, et al.
(författare)
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Constraint Programming in Sweden
- 2009
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Ingår i: IEEE Intelligent Systems. - : IEEE Press. - 1541-1672. ; 24:2, s. 87-89
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Forskningsöversikt (övrigt vetenskapligt/konstnärligt)
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| 10. |
- Frimodig, Sara, et al.
(författare)
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Models for Radiation Therapy Patient Scheduling
- 2019
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Ingår i: 25th International Conference on Principles and Practice of Constraint Programming, CP 2019. - Cham : Springer. - 9783030300470 ; , s. 421-437
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Konferensbidrag (refereegranskat)abstract
- In Europe, around half of all patients diagnosed with cancer are treated with radiation therapy. To reduce waiting times, optimizing the use of linear accelerators for treatment is crucial. This paper introduces an Integer Programming (IP) and two Constraint Programming (CP) models for the non-block radiotherapy patient scheduling problem. Patients are scheduled considering priority, pattern, duration, and start day of their treatment. The models include expected future patient arrivals. Treatment time of the day is included in the models as time windows which enable more realistic objectives and constraints. The models are thoroughly evaluated for multiple different scenarios, altering: planning day, machine availability, arrival rates, patient backlog, and the number of time windows in a day. The results demonstrate that the CP models find feasible solutions earlier, while the IP model reaches optimality considerably faster.
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