Staging memory for massively parallel processor

The invention herein relates to a computer organization capable of rapidly processing extremely large volumes of data. A staging memory is provided having a main stager portion consisting of a large number of memory banks which are accessed in parallel to receive, store, and transfer data words simultaneous with each other. Substager portions interconnect with the main stager portion to match input and output data formats with the data format of the main stager portion. An address generator is coded for accessing the data banks for receiving or transferring the appropriate words. Input and output permutation networks arrange the lineal order of data into and out of the memory banks

SAR processing on the MPP

The processing of synthetic aperture radar (SAR) signals using the massively parallel processor (MPP) is discussed. The fast Fourier transform convolution procedures employed in the algorithms are described. The MPP architecture comprises an array unit (ARU) which processes arrays of data; an array control unit which controls the operation of the ARU and performs scalar arithmetic; a program and data management unit which controls the flow of data; and a unique staging memory (SM) which buffers and permutes data. The ARU contains a 128 by 128 array of bit-serial processing elements (PE). Two-by-four surarrays of PE's are packaged in a custom VLSI HCMOS chip. The staging memory is a large multidimensional-access memory which buffers and permutes data flowing with the system. Efficient SAR processing is achieved via ARU communication paths and SM data manipulation. Real time processing capability can be realized via a multiple ARU, multiple SM configuration

The Incremental Garbage Collection of Processes

Key Words and Phrases: garbage collection, multiprocessing systems, processor scheduling. "lazy evaluation, "eager" evaluation. CR Categories: 3.60, 3.80, 4.13, 4.22, 4.32. This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522. This paper was presented at the AI*PL Conference at Rochester, N.Y. in August, 1977.This paper investigates some problems associated with an argument evaluation order that we call "future" order, which is different from both call-by-name and call-by-value. In call-by-future, each formal parameter of a function is bound to a separate process (called a "future") dedicated to the evaluation of the corresponding argument. This mechanism allows the fully parallel evaluation of arguments to a function, and has been shown to augment the expressive power of a language. We discuss an approach to a problem that arises in this context: futures which were thought to be relevant when they were created become irrelevant through being ignored in the body of the expression where they were bound. The problem of irrelevant processes also appears in multiprocessing problem-solving systems which start several processors working on the same problem but with different methods, and return with the solution which finishes first. This parallel method strategy has the drawback that the processes which are investigating the losing methods must be identified, stopped, and re-assigned to more useful tasks. The solution we propose is that of garbage collection. We propose that the goal structure of the solution plan be explicitly represented in memory as part of the graph memory (like Lisp's heap) so that a garbage collection algorithm can discover which processes are performing useful work, and which can be recycled for a new task. An incremental algorithm for the unified garbage collection of storage and processes is described.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

Faster Approximate String Matching for Short Patterns

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have lengths $m$ and $n$, respectively. On a standard unit-cost word RAM with word size $w \geq \log n$ we present an algorithm using time $$O(nk \cdot \min(\frac{\log^2 m}{\log n},\frac{\log^2 m\log w}{w}) + n)$$ When $P$ is short, namely, $m = 2^{o(\sqrt{\log n})}$ or $m = 2^{o(\sqrt{w/\log w})}$ this improves the previously best known time bounds for the problem. The result is achieved using a novel implementation of the Landau-Vishkin algorithm based on tabulation and word-level parallelism.Comment: To appear in Theory of Computing System

Bacterial and Archaea Community Present in the Pine Barrens Forest of Long Island, NY: Unusually High Percentage of Ammonia Oxidizing Bacteria

Of the few preserved areas in the northeast of United States, the soil in the Pine Barrens Forests presents a harsh environment for the microorganisms to grow and survive. In the current study we report the use of clustering methods to scientifically select the sampling locations that would represent the entire forest and also report the microbial diversity present in various horizons of the soil. Sixty six sampling locations were selected across the forest and soils were collected from three horizons (sampling depths). The three horizons were 0–10 cm (Horizon O); 11–25 cm (Horizon A) and 26–40 cm (Horizon B). Based on the total microbial substrate utilization pattern and K-means clustering analysis, the soil in the Pine Barrens Forest can be classified into four distinct clusters at each of the three horizons. One soil sample from each of the four clusters were selected and archaeal and bacterial populations within the soil studied using pyrosequencing method. The results show the microbial communities present in each of these clusters are different. Within the microbial communities present, microorganisms involved in nitrogen cycle occupy a major fraction of microbial community in the soil. High level of diversity was observed for nitrogen fixing bacteria. In contrast, Nitrosovibrio and Nitrosocaldus spp are the single bacterial and archaeal population respectively carrying out ammonia oxidation in the soil

Sequence of bronchoalveolar lavage and histopathologic findings in rat lungs early in inhalation asbestos exposure

To assess the early cellular inflammatory response of the lungs, 7 rats per group were exposed nose-only to 13 mg/m3 of chrysotile asbestos, 7 h/day for 2, 4, or 6 wk. Lung histopathology and bronchoalveolar lavage (BAL) were analyzed. In exposed animals, dose-related bronchiolitis and fibrosis were found that were not seen in control rats (p less than 0.001). In exposed rats, total BAL cells were increased six-to sevenfold over matched controls, and more cells were retrieved with longer exposure (p less than 0.001). In the BAL, counts of macrophages, lymphocytes, and polymorphonuclear cells (PMNs) were each elevated in the exposed rats (each p less than 0.001). PMNs seen histologically and in the BAL may be related to the time period examined. PMNs and lymphocytes observed throughout this 6-wk study support the idea that these cells may have an important role in the early events of asbestos lung injury

Sorting networks and their applications

To achieve high throughput rates today's computers perform several operations simultaneously. Not only are I/O operations performed concurrently with computing, but also, in multiprocessors, several computin

Architecture of a massively parallel processor

The massively parallel processor (MPP) system is designed to process satellite imagery at high rates. A large number (16,384) of processing elements (PE\u27s) are configured in a square array. For optimum performance on operands of arbitrary length, processing is performed in a bit-serial manner. On 8-bit integer data, addition can occur at 6553 million operations per second (MOPS) and multiplication at 1861 MOPS. On 32-bit floating-point data, addition can occur at 430 MOPS and multiplication at 216 MOPS.</p