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Background Real-time analysis of patient data during medical procedures can provide vital diagnostic feedback that significantly improves chances of success. With sensors becoming increasingly fast, frameworks such as Deep Neural Networks are required to perform calculations within the strict timing constraints for real-time operation. However, traditional computing platforms responsible for running...
FPGAs are becoming an attractive choice as a heterogeneous computing unit for scientific computing because FPGA vendors are adding floating-point-optimized architectures to their product lines. Additionally, high-level synthesis (HLS) tools such as Altera OpenCL SDK are emerging, which could potentially break the FPGA programming wall and provide a streamlined flow for domain experts in scientific...
Exascale systems are expected to feature hundreds of thousands of compute nodes with hundreds of hardware threads and complex memory hierarchies with a mix of on-package and persistent memory modules. In this context, the Argo project is developing a new operating system for exascale machines. Targeting production workloads using workflows or coupled codes, we improve the Linux kernel on several fronts...
Energy and power consumption are major limitations to continued scaling of computing systems. Inexactness where the quality of the solution can be traded for energy savings has been proposed as a counterintuitive approach to overcoming those limitation. However, in the past, inexactness has been necessitated the need for highly customized or specialized hardware. In order to move away from customization,...
The Argo project is a DOE initiative for designing a modular operating system/runtime for the next generation of supercomputers. A key focus area in this project is power management, which is one of the main challenges on the path to exascale. In this paper, we discuss ideas for systemwide power management in the Argo project. We present a hierarchical and scalable approach to maintain a power bound...
Thermal overheating is a serious concern in modern supercomputing systems. Elevated temperature levels reduce the reliability and the lifetime of the underlying hardware and increase their power consumption. Previous studies on mitigating thermal hotspots at the hardware and run-time system levels have typically used approaches that trade off performance for reduced operating temperatures. In this...
The recently released MPI-3.0 standard introduced a process-level shared-memory interface which enables processes within the same node to have direct load/store access to each others' memory. Such an interface allows applications to declare data structures that are shared by multiple MPI processes on the node. In this paper, we study the capabilities and performance implications of using MPI-3.0 shared...
Future exascale systems will impose several conflicting challenges on the operating system (OS) running on the compute nodes of such machines. On the one hand, the targeted extreme scale requires the kind of high resource usage efficiency that is best provided by lightweight OSes. At the same time, substantial changes in hardware are expected for exascale systems. Compute nodes are expected to host...
Current Monte Carlo neutron transport applications use continuous energy cross section data to provide the statistical foundation for particle trajectories. This "classical" algorithm requires storage and random access of very large data structures. Recently, Forget et al.[1] reported on a fundamentally new approach, based on multipole expansions, that distills cross section data down to...
Power consumption is becoming a critical factor as we continue our quest toward exascale computing. Yet, actual power utilization of a complete system is an insufficiently studied research area. Estimating the power consumption of a large scale system is a nontrivial task because a large number of components are involved and because power requirements are affected by the (unpredictable) workloads...
Data centers' energy consumption has attracted global attention because of the fast growth of the information technology (IT) industry. Up to 60% of the energy consumed in a data center is used for cooling in wasteful ways as a result of lack of environmental information and overcompensated cooling systems. In this project, a wireless sensor network for data-enter environmental monitoring was developed...
Current leadership-class machines suffer from a significant imbalance between their computational power and their I/O bandwidth. I/O forwarding is a paradigm that attempts to bridge the increasing performance and scalability gap between the compute and I/O components of leadership-class machines to meet the requirements of data-intensive applications by shipping I/O calls from compute nodes to dedicated...
We investigate operating system noise, which we identify as one of the main reasons for a lack of synchronicity in parallel applications. Using a microbenchmark, we measure the noise on several contemporary platforms and find that, even with a general-purpose operating system, noise can be limited if certain precautions are taken. We then inject artificially generated noise into a massively parallel...
We investigate operating system noise, which we identify as one of the main reasons for a lack of synchronicity in parallel applications. Using a microbenchmark, we measure the noise on several contemporary platforms and find that, even with a general-purpose operating system, noise can be limited if certain precautions are taken. We then inject artificially generated noise into a massively parallel...
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