The demonstration here of multiple tubercles in the pleura of patients with tuberculous effusion would tend to indicate that direct pleural involvement in tuberculous pleural effusion is far more extensive than previously believed. Schuman 10 cites Jacobeus as noting multiple pleural tubercles in patients with effusion who were ex¬ amined by thoracoscopy. Auerbach (see table).Furthermore, there is no evidence that hypertension played a role in this disease process.

No abstract

Nowadays, HPC systems frequently emerge as clusters of commodity processors with attached accelerators. Moving from tedious low-level accelerator programming to increased development productivity, the directive-based programming models OpenACC and OpenMP are promising candidates. While OpenACC was completed about two years ago, OpenMP just recently added support for accelerator programming. To assist developers in their decision-making which approach to take, we compare both models with respect to their programmability. Besides investigating their expressiveness by putting their constructs side by side, we focus on the evaluation of their power based on structured parallel programming patterns (aka algorithmic skeletons). These patterns describe the basic entities of parallel algorithms of which we cover the patterns map, stencil, reduction, fork-join, superscalar sequence, nesting and geometric decomposition. Architectural targets of this work are NVIDIA-type accelerators (GPUs) and specialties of Intel-type accelerators (Xeon Phis). Additionally, we assess the prospects of OpenACC and OpenMP concerning future development in soft-and hardware design.

No abstract

The use of GPU accelerators is becoming common in HPC platforms due to the their effective performance and energy efficiency. In addition, new generations of multicore processors are being designed with wider vector units and/or larger hardware thread counts, also contributing to the peak performance of the whole system. Although current directive-based paradigms, such as OpenMP or OpenACC, support both accelerators and multicore-based hosts, they do not provide an effective and efficient way to concurrently use them, usually resulting in accelerated programs in which the potential computational performance of the host is not exploited. In this paper we propose an extension to the OpenMP 4.5 directive-based programming model to support the specification and execution of multiple instances of task regions on different devices (i.e. accelerators in conjunction with the vector and heavily multithreaded capabilities in multicore processors). The compiler is responsible for the generation of device-specific code for each device kind, delegating to the runtime system the dynamic schedule of the tasks to the available devices. The new proposed clause conveys useful insight to guide the scheduler while keeping a clean, abstract and machine independent programmer interface. The potential of the proposal is analyzed in a prototype implementation in the OmpSs compiler and runtime infrastructure. Performance evaluation is done using three kernels (N-Body, tiled matrix multiply and Stream) on different GPU-capable systems based on ARM, Intel x86 and IBM Power8. From the evaluation we observe speed-ups in the 8-20% range compared to versions in which only the GPU is used, reaching 96% of the additional peak performance thanks to the reduction of data transfers and the benefits introduced by the OmpSs NUMA-aware scheduler.