The anti-Greek riot of 1909: South Omaha

The anti-Greek riot of 1909, in South Omaha, Nebraska, was a violent, regrettable, but significant episode in American history. Its importance rests in the fact that it took place at a time when the American people were in the process of making a very important decision concerning immigration. By 1908, the problem of the oriental immigrant entering and living on the west coast of the United States had been solved largely by adopting a policy of exclusion. There still remained, however, the great wave of the new immigration from southern and eastern Europe. The American native, largely of northwestern European and Protestant stock, was faced with the decision of selecting a policy toward the new immigrant, whose cultural background was comparatively foreign

GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP

Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, the projections were that simulation demands would scale linearly with luminosity increase, compensated only partially by an increase of computing resources. The extension of fast simulation approaches to more use cases, covering a larger fraction of the simulation budget, is only part of the solution due to intrinsic precision limitations. The remainder corresponds to speeding-up the simulation software by several factors, which is out of reach using simple optimizations on the current code base. In this context, the GeantV R&D project was launched, aiming to redesign the legacy particle transport codes in order to make them benefit from fine-grained parallelism features such as vectorization, but also from increased code and data locality. This paper presents extensively the results and achievements of this R&D, as well as the conclusions and lessons learnt from the beta prototype.Comment: 34 pages, 26 figures, 24 table

DPM evolution: a disk operations management engine for DPM

The DPM (Disk Pool Manager) project is the most widely deployed solution for storage of large data repositories on Grid sites, and is completing the most important upgrade in its history, with the aim of bringing important new features, performance and easier long term maintainability. Work has been done to make the so-called “legacy stack” optional, and substitute it with an advanced implementation that is based on the fastCGI and RESTful technologies. Beside the obvious gain in making optional several legacy components that are difficult to maintain, this step brings important features together with performance enhancements. Among the most important features we can cite the simplification of the configuration, the possibility of working in a totally SRM-free mode, the implementation of quotas, free/used space on directories, and the implementation of volatile pools that can pull files from external sources, which can be used to deploy data caches. Moreover, the communication with the new core, called DOME (Disk Operations Management Engine) now happens through secure HTTPS channels through an extensively documented, industry-compliant protocol. For this leap, referred to with the codename “DPM Evolution”, the help of the DPM collaboration has been very important in the beta testing phases, and here we report about the technical choices

Towards a high performance geometry library for particle-detector simulations

Thread-parallelisation and single-instruction multiple data (SIMD) ”vectorisation” of software components in HEP computing has become a necessity to fully benefit from current and future computing hardware. In this context, the Geant-Vector/GPU simulation project aims to re-engineer current software for the simulation of the passage of particles through detectors in order to increase the overall event throughput. As one of the core modules in this area, the geometry library plays a central role and vectorising its algorithms will be one of the cornerstones towards achieving good CPU performance. Here, we report on the progress made in vectorising the shape primitives, as well as in applying new C++ template based optimisations of existing code available in the Geant4, ROOT or USolids geometry libraries. We will focus on a presentation of our software development approach that aims to provide optimised code for all use cases of the library (e.g., single particle and many-particle APIs) and to support different architectures (CPU and GPU) while keeping the code base small, manageable and maintainable. We report on a generic and templated C++ geometry library as a continuation of the AIDA USolids project. The experience gained with these developments will be beneficial to other parts of the simulation software, such as for the optimisation of the physics library, and possibly to other parts of the experiment software stack, such as reconstruction and analysis

First experience of vectorizing electromagnetic physics models for detector simulation

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. The GeantV vector prototype for detector simulations has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth, parallelization needed to achieve optimal performance or memory access latency and speed. An additional challenge is to avoid the code duplication often inherent to supporting heterogeneous platforms. In this paper we present the first experience of vectorizing electromagnetic physics models developed for the GeantV project

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. This work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

The GeantV project is focused on the R&D; of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. This work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results