Personal Multi-threading

Multi-threading allows agents to pursue a heterogeneous collection of tasks in an orderly manner. The view of multi-threading that emerges from thread algebra is applied to the case where a single agent, who may be human, maintains a hierarchical multithread as an architecture of its own activities

Micro-threading and FPGA implementation of a RISC microprocessor : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Palmerston North, New Zealand

Appendix E removed due to copyright restrictions. Articles are available in the print copy held in the libraryThis thesis is the outcome of research in two areas of computer technology: microprocessor and multi-processor architectures (specifically from the perspective of how differently they tolerate highly-latent and non-deterministic events), and hardware design of complex digital systems containing both datapath and control (particularly microprocessors). This thesis starts by pointing out that in order to achieve high processing speeds, current popular superscalar microprocessors (e.g. Intel Pentiums, Digital Alpha, etc) rely heavily on the technique of speculating the outcome of instruction flow in order to predict the behaviour of non-deterministic computing operations (as in loading operands from high-latency memory into the processor). This is fine only if the speculation is correct. But, what if it isn't? If the speculation fails, this would mean that the processor has to abandon its current decision (which now proved to be the wrong one) for the instruction flow path taken and to start all over again with the other path (the actual correct one). This is a waste of valuable processing time and hardware resources and a reduction of performance when speculation fails. Therefore, these processors can achieve high performance only when the majority of speculations are successful (being able to predict the right path). In an attempt to overcome the above shortcomings, the first part of this thesis is an investigation of the novel vector micro-threading architecture as an alternative approach to the current superscalar-based speculative microprocessor designs. Micro-threading is based on the not-so-novel multithreading technique, which avoids speculation altogether and instead, starts running a different thread of instructions while waiting for the non-determinism to be resolved. This utilizes the chip resources more efficiently without waste of any processing power. The rest of this thesis focuses on the baseline RISC processor platform, the MIPS R2000, which is reviewed first then partially synthesized from the RTL (Register Transfer Level) description using VHDL and then simulated and tested. This is conducted in order for future research to build upon and add the micro-threading architectural add-ons and modifications. Keywords: Micro-threading, Latency Tolerance, FPGA Synthesis, RISC Architecture, MIPS R2000 processor, VHDL

Methodological issues in developing a multi-dimensional coding procedure for small group chat communication

In CSCL research, collaboration through chat has primarily been studied in dyadic settings. This article discusses three issues that emerged during the development of a multi-dimensional coding procedure for small group chat communication: a) the unit of analysis and unit fragmentation, b) the reconstruction of the response structure and c) determining reliability without overestimation. Threading, i.e. connections between analysis units, proved essential to handle unit fragmentation, to reconstruct the response structure and for reliability of coding. In addition, a risk for reliability overestimation was illustrated. Implications for analysis methodology in CSCL are discussed

Multidimensional Range Queries on Modern Hardware

Range queries over multidimensional data are an important part of database workloads in many applications. Their execution may be accelerated by using multidimensional index structures (MDIS), such as kd-trees or R-trees. As for most index structures, the usefulness of this approach depends on the selectivity of the queries, and common wisdom told that a simple scan beats MDIS for queries accessing more than 15%-20% of a dataset. However, this wisdom is largely based on evaluations that are almost two decades old, performed on data being held on disks, applying IO-optimized data structures, and using single-core systems. The question is whether this rule of thumb still holds when multidimensional range queries (MDRQ) are performed on modern architectures with large main memories holding all data, multi-core CPUs and data-parallel instruction sets. In this paper, we study the question whether and how much modern hardware influences the performance ratio between index structures and scans for MDRQ. To this end, we conservatively adapted three popular MDIS, namely the R*-tree, the kd-tree, and the VA-file, to exploit features of modern servers and compared their performance to different flavors of parallel scans using multiple (synthetic and real-world) analytical workloads over multiple (synthetic and real-world) datasets of varying size, dimensionality, and skew. We find that all approaches benefit considerably from using main memory and parallelization, yet to varying degrees. Our evaluation indicates that, on current machines, scanning should be favored over parallel versions of classical MDIS even for very selective queries

Load sharing for optimistic parallel simulations on multicore machines

Parallel Discrete Event Simulation (PDES) is based on the partitioning of the simulation model into distinct Logical Processes (LPs), each one modeling a portion of the entire system, which are allowed to execute simulation events concurrently. This allows exploiting parallel computing architectures to speedup model execution, and to make very large models tractable. In this article we cope with the optimistic approach to PDES, where LPs are allowed to concurrently process their events in a speculative fashion, and rollback/ recovery techniques are used to guarantee state consistency in case of causality violations along the speculative execution path. Particularly, we present an innovative load sharing approach targeted at optimizing resource usage for fruitful simulation work when running an optimistic PDES environment on top of multi-processor/multi-core machines. Beyond providing the load sharing model, we also define a load sharing oriented architectural scheme, based on a symmetric multi-threaded organization of the simulation platform. Finally, we present a real implementation of the load sharing architecture within the open source ROme OpTimistic Simulator (ROOT-Sim) package. Experimental data for an assessment of both viability and effectiveness of our proposal are presented as well. Copyright is held by author/owner(s)

The SCC and the SICSA multi-core challenge

Two phases of the SICSA Multi-core Challenge have gone past. The first challenge was to produce concordances of books for sequences of words up to length N; and the second to simulate the motion of N celestial bodies under gravity. We took both challenges on the SCC, using C and the Linux Shell. This paper is an account of the experiences gained. It also gives a shorter account of the performance of other systems on the same set of problems, as they provide benchmarks against which the SCC performance can be compared with