Characterizing Sources of Ineffectual Computations in Deep Learning Networks

Hardware accelerators for inference with neural networks can take advantage of the properties of data they process. Performance gains and reduced memory bandwidth during inference have been demonstrated by using narrower data types [1] [2] and by exploiting the ability to skip and compress values that are zero [3]-[6]. Similarly useful properties have been identified at a lower-level such as varying precision requirements [7] and bit-level sparsity [8] [9]. To date, the analysis of these potential sources of superfluous computation and communication has been constrained to a small number of older Convolutional Neural Networks (CNNs) used for image classification. It is an open question as to whether they exist more broadly. This paper aims to determine whether these properties persist in: (1) more recent and thus more accurate and better performing image classification networks, (2) models for image applications other than classification such as image segmentation and low-level computational imaging, (3) Long-Short-Term-Memory (LSTM) models for non-image applications such as those for natural language processing, and (4) quantized image classification models. We demonstrate that such properties persist and discuss the implications and opportunities for future accelerator designs

Multiple metal contamination from house paints: consequences of power sanding and paint scraping in New Orleans.

Power sanding exterior paint is a common practice during repainting of old houses in New Orleans, Louisiana, that triggers lead poisoning and releases more than Pb. In this study we quantified the Pb, zinc, cadmium, manganese, nickel, copper, cobalt, chromium, and vanadium in exterior paint samples collected from New Orleans homes (n = 31). We used interior dust wipes to compare two exterior house-painting projects. House 1 was measured in response to the plight of a family after a paint contractor power sanded all exterior paint from the weatherboards. The Pb content (approximately 130,000 microg Pb/g) was first realized when the family pet died; the children were hospitalized, the family was displaced, and cleanup costs were high. To determine the quantity of dust generated by power sanding and the benefits of reducing Pb-contaminated dust, we tested a case study house (house 2) for Pb (approximately 90,000 microg/g) before the project was started; the house was then dry scraped and the paint chips were collected. Although the hazards of Pb-based paints are well known, there are other problems as well, because other toxic metals exist in old paints. If house 2 had been power sanded to bare wood like house 1, the repainting project would have released as dust about 7.4 kg Pb, 3.5 kg Zn, 9.7 g Cd, 14.8 g Cu, 8.8 g Mn, 1.5 g Ni, 5.4 g Co, 2.4 g Cr, and 0.3 g V. The total tolerable daily intake (TTDI) for a child under 6 years of age is 6 microg Pb from all sources. Converting 7.4 kg Pb to this scale is vexing--more than 1 billion (10(9)) times the TTDI. Also for perspective, the one-time release of 7.4 x 10(9) microg of Pb dust from sanding compares to 50 x 10(9) microg of Pb dust emitted annually per 0.1 mile (0.16 km) from street traffic during the peak use of leaded gasoline. In this paper, we broaden the discussion to include an array of metals in paint and underscore the need and possibilities for curtailing the release of metal dust