El artículo tiene el propósito de mostrar algunos análisis y observaciones preliminares sobre el problema de la criminalidad en Medellín y sobre el mucho más complejo problema de la respuesta institucional y social al fenómeno. Se alude a las relaciones entre decisiones políticas propias de este ámbito y las que, real o simbólicamente, apuntan a conjurar problemas de una índole que trascienden. Ello, de paso, remite al problema de la subordinación o superposición de otras decisiones políticas o de políticas publicas referidas a problemáticas distintas de la cuestión criminal.
Parallel task-based programming models, like OpenMP, allow application developers to easily create a parallel version of their sequential codes. The standard OpenMP 4.0 introduced the possibility of describing a set of data dependences per task that the runtime uses to order the tasks execution. This order is calculated using shared graphs, which are updated by all threads in exclusive access using synchronization mechanisms (locks) to ensure the dependence management correctness. The contention in the access to these structures becomes critical in many-core systems because several threads may be wasting computation resources waiting their turn. This paper proposes an asynchronous management of the runtime structures, like task dependence graphs, suitable for task-based programming model runtimes. In such organization, the threads request actions to the runtime instead of doing them directly. The requests are then handled by a distributed runtime manager (DDAST) which does not require dedicated resources. Instead, the manager uses the idle threads to modify the runtime structures. The paper also presents an implementation, analysis and performance evaluation of such runtime organization. The performance results show that the proposed asynchronous organization outperforms the speedup obtained by the original runtime for different benchmarks and different many-core architectures. ; This work is partially supported by the European Union H2020 Research and Innovation Action (projects 801051, 754337 and 780681), by the Spanish Government (projects SEV-2015-0493 and TIN2015-65316-P, grant BES-2016-078046), and by the Generalitat de Catalunya (contracts 2017-SGR-1414 and 2017-SGR-1328). ; Peer Reviewed ; Postprint (author's final draft)
OmpSs is a programming model that provides a simple and powerful way of annotating sequential programs to exploit heterogeneity and task parallelism based on runtime data dependency analysis, dataflow scheduling and out-of-order task execution; it has greatly influenced Version 4.0 of the OpenMP standard. The current implementation of OmpSs achieves those capabilities with a pure-software runtime library: Nanos++. Therefore, although powerful and easy to use, the performance benefits of exploiting fine-grained (pico) task parallelism are limited by the software runtime overheads. To overcome this handicap we propose Picos, an implementation of the Task Superscalar (TSS) architecture that provides hardware support to the OmpSs programming model. Picos is a novel hardware dataflow-based task scheduler that dynamically analyzes inter-task dependencies and identifies task-level parallelism at run-time. In this paper, we describe the Picos Hardware Design and the latencies of the main functionality of its components, based on the synthesis of their VHDL design. We have implemented a full cycle-accurate simulator based on those latencies to perform a design exploration of the characteristics and number of its components in a reasonable amount of time. Finally, we present a comparison of the Picos and Nanos++ runtime performance scalability with a set of real benchmarks. With Picos, a programmer can achieve ideal scalability using aggressive parallel strategies with a large number of fine granularity tasks. ; This work is supported by the Spanish Government through Programa Severo Ochoa (SEV-2011-0067), by the Spanish Ministry of Science and Technology through TIN2012-34557 project, by the Generalitat de Catalunya (contract 2009-SGR-980), by the European FP7 project TERAFLUX id. 249013 and by the European Research Council under the European Union's 7th FP, ERC Grant Agreement number 321253. We also thank the Xilinx University Program for its hardware and software donations. ; Peer Reviewed ; Postprint (author's final draft)
OmpSs is a programming model that provides a simple and powerful way of annotating sequential programs to exploit heterogeneity and task parallelism based on runtime data dependency analysis, dataflow scheduling and out-of-order task execution; it has greatly influenced Version 4.0 of the OpenMP standard. The current implementation of OmpSs achieves those capabilities with a pure-software runtime library: Nanos++. Therefore, although powerful and easy to use, the performance benefits of exploiting fine-grained (pico) task parallelism are limited by the software runtime overheads. To overcome this handicap we propose Picos, an implementation of the Task Superscalar (TSS) architecture that provides hardware support to the OmpSs programming model. Picos is a novel hardware dataflow-based task scheduler that dynamically analyzes inter-task dependencies and identifies task-level parallelism at run-time. In this paper, we describe the Picos Hardware Design and the latencies of the main functionality of its components, based on the synthesis of their VHDL design. We have implemented a full cycle-accurate simulator based on those latencies to perform a design exploration of the characteristics and number of its components in a reasonable amount of time. Finally, we present a comparison of the Picos and Nanos++ runtime performance scalability with a set of real benchmarks. With Picos, a programmer can achieve ideal scalability using aggressive parallel strategies with a large number of fine granularity tasks. ; This work is supported by the Spanish Government through Programa Severo Ochoa (SEV-2011-0067), by the Spanish Ministry of Science and Technology through TIN2012-34557 project, by the Generalitat de Catalunya (contract 2009-SGR-980), by the European FP7 project TERAFLUX id. 249013 and by the European Research Council under the European Union's 7th FP, ERC Grant Agreement number 321253. We also thank the Xilinx University Program for its hardware and software donations. ; Peer Reviewed ; Postprint (author's final draft)
This paper presents the new features of the OmpSs@FPGA framework. OmpSs is a data-flow programming model that supports task nesting and dependencies to target asynchronous parallelism and heterogeneity. OmpSs@FPGA is the extension of the programming model addressed specifically to FPGAs. OmpSs environment is built on top of Mercurium source to source compiler and Nanos++ runtime system. To address FPGA specifics Mercurium compiler implements several FPGA related features as local variable caching, wide memory accesses or accelerator replication. In addition, part of the Nanos++ runtime has been ported to hardware. Driven by the compiler this new hardware runtime adds new features to FPGA codes, such as task creation and dependence management, providing both performance increases and ease of programming. To demonstrate these new capabilities, different high performance benchmarks have been evaluated over different FPGA platforms using the OmpSs programming model. The results demonstrate that programs that use the OmpSs programming model achieve very competitive performance with low to moderate porting effort compared to other FPGA implementations. ; This work has received funding from EuroEXA project (European Union's Horizon 2020 Research and Innovation Programme, under grant agreement No 754337), from Spanish Government (projects PID2019-107255GB and SEV-2015- 0493, grant BES-2016-078046), and Generalitat de Catalunya (contracts 2017-SGR-1414 and 2017-SGR-1328). ; Peer Reviewed ; Postprint (author's final draft)
Cyber-Physical Systems (CPSs) are widely used in many applications that require interactions between humans and their physical environment. These systems usually integrate a set of hardware-software components for optimal application execution in terms of performance and energy consumption. The AXIOM project (Agile, eXtensible, fast I/O Module), presented in this paper, proposes a hardware-software platform for CPS coupled with an easy parallel programming model and sufficient connectivity so that the performance can scale-up by adding multiple boards. AXIOM supports a task-based programming model based on OmpSs and leverages a high-speed, inexpensive communication interface called AXIOM-Link. The board also tightly couples the CPU with reconfigurable resources to accelerate portions of the applications. As case studies, AXIOM uses smart video surveillance, and smart home living applications ; This work is partially supported by the European Union H2020 program through the AXIOM project (grant ICT-01-2014 GA 645496) and HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, and by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). We also thank the Xilinx University Program for its hardware and software donations. ; Peer Reviewed ; Postprint (author's final draft)
Cyber-Physical Systems (CPSs) are widely used in many applications that require interactions between humans and their physical environment. These systems usually integrate a set of hardware-software components for optimal application execution in terms of performance and energy consumption. The AXIOM project (Agile, eXtensible, fast I/O Module), presented in this paper, proposes a hardware-software platform for CPS coupled with an easy parallel programming model and sufficient connectivity so that the performance can scale-up by adding multiple boards. AXIOM supports a task-based programming model based on OmpSs and leverages a high-speed, inexpensive communication interface called AXIOM-Link. The board also tightly couples the CPU with reconfigurable resources to accelerate portions of the applications. As case studies, AXIOM uses smart video surveillance, and smart home living applications ; This work is partially supported by the European Union H2020 program through the AXIOM project (grant ICT-01-2014 GA 645496) and HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, and by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). We also thank the Xilinx University Program for its hardware and software donations. ; Peer Reviewed ; Postprint (author's final draft)
