The communication processor of TUMULT-64

Tumult (Twente University MULTi-processor system) is a modular extendible multi-processor system designed and implemented at the Twente University of Technology in co-operation with Oce Nederland B.V. and the Dr. Neher Laboratories (Dutch PTT). Characteristics of the hardware are: MIMD type, distributed memory, message passing, high performance, real-time and fault tolerant. A distributed real-time operating system has been realized, consisting of a multi-tasking kernel per node, inter process communication via typed messages and a distributed file system. In this paper first a brief description of the system is given, after that the architecture of the communication processor will be discussed. Reduction of the communication overhead due to message passing will be emphasized.\ud \u

Throughput of Streaming Applications Running on a Multiprocessor Architecture

We study the timing behaviour of streaming applications running on a multiprocessor architecture. Dependencies are derived between the application throughput and the timing characteristics of the processors and communication. Four different processor organizations that strongly influenced the results are considered and compared

Efficient Inter-Task Communication for Nested Loop Programs on a Multiprocessor System

In modern multiprocessor systems, processors can be stalled by inter-task communication when reading from a remote buffer. This paper presents a solution for the inter-task communication, that has a minimal impact on the performance of the system, hides the inter-task communication latency without requiring additional hardware. The solution applies to jobs, represented as task graphs, where the tasks are nested loop programs. Buffers are allocated in scratch-pad memories of the consuming tasks to provide low latency read access. For the nested loop programs, minimal buffer sizes can be determined to cover all possible communication patterns. The added computational complexity is low, as the solution adds only a few operations to the nested loop programs

Modeling the Temperature Bias of Power Consumption for Nanometer-Scale CPUs in Application Processors

We introduce and experimentally validate a new macro-level model of the CPU temperature/power relationship within nanometer-scale application processors or system-on-chips. By adopting a holistic view, this model is able to take into account many of the physical effects that occur within such systems. Together with two algorithms described in the paper, our results can be used, for instance by engineers designing power or thermal management units, to cancel the temperature-induced bias on power measurements. This will help them gather temperature-neutral power data while running multiple instance of their benchmarks. Also power requirements and system failure rates can be decreased by controlling the CPU's thermal behavior. Even though it is usually assumed that the temperature/power relationship is exponentially related, there is however a lack of publicly available physical temperature/power measurements to back up this assumption, something our paper corrects. Via measurements on two pertinent platforms sporting nanometer-scale application processors, we show that the power/temperature relationship is indeed very likely exponential over a 20{\deg}C to 85{\deg}C temperature range. Our data suggest that, for application processors operating between 20{\deg}C and 50{\deg}C, a quadratic model is still accurate and a linear approximation is acceptable.Comment: Submitted to SAMOS 2014; International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS XIV

Interacting Agents and Continuous Opinions Dynamics

We present a model of opinion dynamics in which agents adjust continuous opinions as a result of random binary encounters whenever their difference in opinion is below a given threshold. High thresholds yield convergence of opinions towards an average opinion, whereas low thresholds result in several opinion clusters. The model is further generalised to network interactions, threshold heterogeneity, adaptive thresholds and binary strings of opinions.Comment: 21 pages, 13 figures. http://www.lps.ens.fr/~weisbuch/contopidyn/contopidyn.htm