There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

The PASCAL Visual Object Classes Challenge

IEEE Transactions on Pattern Analysis and Machine Intelligence

In the field of HPC, the current hardware trend is to design multiprocessor architectures featuring heterogeneous technologies such as specialized coprocessors (e.g. Cell/BE) or data-parallel accelerators (e.g. GPUs). Approaching the theoretical performance of these architectures is a complex issue. Indeed, substantial efforts have already been devoted to efficiently offload parts of the computations. However, designing an execution model that unifies all computing units and associated embedded memory remains a main challenge. We therefore designed StarPU, an original runtime system providing a high-level, unified execution model tightly coupled with an expressive data management library. The main goal of StarPU is to provide numerical kernel designers with a convenient way to generate parallel tasks over heterogeneous hardware on the one hand, and easily develop and tune powerful scheduling algorithms on the other hand. We have developed several strategies that can be selected seamlessly at run-time, and we have analyzed their efficiency on several algorithms running simultaneously over multiple cores and a GPU. In addition to substantial improvements regarding execution times, we have obtained consistent superlinear parallelism by actually exploiting the heterogeneous nature of the machine. We eventually show that our dynamic approach competes with the highly optimized MAGMA library and overcomes the limitations of the corresponding static scheduling in a portable way. Copyright © 2010 John Wiley & Sons, Ltd.

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StarPU: a unified platform for task scheduling on heterogeneous multicore architectures

Communications of the ACM (CACM for short, not the best sounding acronym around) is the ACM’s flagship magazine. Started in 1957, CACM is handy for keeping up to date on current research being carried out across all topics of computer science and realworld applications. CACM has had an illustrious past with many influential pieces of work and debates started within its pages. These include Hoare’s presentation of the Quicksort algorithm; Rivest, Shamir and Adleman’s description of the first publickey cryptosystem RSA; and Dijkstra’s famous letter against the use of GOTO. In addition to the print edition, which is released monthly, there is a fantastic website (http://cacm.acm. org/) that showcases not only the most recent edition but all previous CACM articles as well, readable online as well as downloadable as a PDF. In addition, the website lets you browse for articles by subject, a handy feature if you want to focus on a particular topic. CACM is really essential reading. Pretty much guaranteed to contain content that is interesting to anyone, it keeps tabs on the latest in computer science. It is a valuable asset for us students, who tend to delve deep into a particular area of CS and forget everything that is happening around us. — Daniel Gooch U ndergraduate research is like a box of chocolates: You never know what kind of project you will get. That being said, there are still a few things you should know to get the most out of the experience.

Communications of the ACM

Programming for large-scale, multicore-based architectures requires adequate tools that offer ease of programming and do not hinder application performance. StarSs is a family of parallel programming models based on automatic function-level parallelism that targets productivity. StarSs deploys a data-flow model: it analyzes dependencies between tasks and manages their execution, exploiting their concurrency as much as possible.

This paper introduces Cluster Superscalar (ClusterSs), a new StarSs member designed to execute on clusters of SMPs (Symmetric Multiprocessors). ClusterSs tasks are asynchronously created and assigned to the available resources with the support of the IBM APGAS runtime, which provides an efficient and portable communication layer based on one-sided communication.

We present the design of ClusterSs on top of APGAS, as well as the programming model and execution runtime for Java applications. Finally, we evaluate the productivity of ClusterSs, both in terms of programmability and performance and compare it to that of the IBM X10 language. Copyright © 2012 John Wiley & Sons, Ltd.

A high-productivity task-based programming model for clusters

We employ the dynamic runtime system OmpSs to decrease the overhead of data motion in the now ubiquitous non-uniform memory access NUMA high concurrency environment of multicore processors. The dense numerical linear algebra algorithms of Cholesky factorization and symmetric matrix inversion are employed as representative benchmarks. Work stealing occurs within an innovative NUMA-aware scheduling policy to reduce data movement between NUMA nodes. The overall approach achieves separation of concerns by abstracting the complexity of the hardware from the end users so that high productivity can be achieved. Performance results on a large NUMA system outperform the state-of-the-art existing implementations up to a two fold speedup for the Cholesky factorization, as well as the symmetric matrix inversion, while the OmpSs-enabled code maintains strong similarity to its original sequential version.

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Dense Matrix Computations on NUMA Architectures with Distance-Aware Work Stealing

GRID superscalar is a Grid programming environment that enables one to parallelize the execution of sequential applications in computational Grids. The run-time library automatically builds a task data-dependence graph of the application and it can be seen as an implicit workflow system. The current interface supports C/C++ and Perl applications. The run-time library is based on Globus Toolkit 2.x using GRAM and GSIFTP services. In this document we describe the GRID superscalar basics emphasizing those aspects related to Grid workflow, in particular the flexibility of using an imperative language to describe the application. Copyright © 2005 John Wiley & Sons, Ltd.

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Automatic Grid workflow based on imperative programming languages

c © 2006 by John von Neumann Institute for Computing Permission to make digital or hard copies of portions of this work for personal or classroom use is granted provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise requires prior specific permission by the publisher mentioned above.

Scalability of Visualization and Tracing Tools

This paper discusses the issues related to the accuracy of performance prediction tools for message passing programs. We present the results of two sets of experiments to quantify the effect of the instrumentation overhead and variance in the accuracy of Dimemas. The results show that this performance prediction tool can be used with a high level of confidence as the effect of instrumentation overhead on the predicted performance is minimal. We also show that it is possible to carry out instrumentation runs in highly loaded multi-user environments and still be able to accurately analyze the performance of the application as if it had run alone.

Jesús Labarta

Papers

A high-productivity task-based programming model for clusters

Dense Matrix Computations on NUMA Architectures with Distance-Aware Work Stealing

Automatic Grid workflow based on imperative programming languages

Scalability of Visualization and Tracing Tools

Sensitivity of Performance Prediction of Message Passing Programs