47 citations · 63 across the 5 of their papers we have counts for
7 papers
LoopStack: a Lightweight Tensor Algebra Compiler Stack
Bram Wasti, José Pablo Cambronero, Benoit Steiner +2
We present LoopStack, a domain specific compiler stack for tensor operations, composed of a frontend, LoopTool, and an efficient optimizing code generator, LoopNest. This stack ena…
Large-scale image segmentation based on distributed clustering algorithms
Ran Lu, Aleksandar Zlateski, H. Sebastian Seung
Many approaches to 3D image segmentation are based on hierarchical clustering of supervoxels into image regions. Here we describe a distributed algorithm capable of handling a trem…
L3 Fusion: Fast Transformed Convolutions on CPUs
Rati Gelashvili, Nir Shavit, Aleksandar Zlateski
Fast convolutions via transforms, either Winograd or FFT, had emerged as a preferred way of performing the computation of convolutional layers, as it greatly reduces the number of…
PZnet: Efficient 3D ConvNet Inference on Manycore CPUs
Sergiy Popovych, Davit Buniatyan, Aleksandar Zlateski +2
Convolutional nets have been shown to achieve state-of-the-art accuracy in many biomedical image analysis tasks. Many tasks within biomedical analysis domain involve analyzing volu…
FFT Convolutions are Faster than Winograd on Modern CPUs, Here is Why
Aleksandar Zlateski, Zhen Jia, Kai Li +1
Winograd-based convolution has quickly gained traction as a preferred approach to implement convolutional neural networks (ConvNet) on various hardware platforms because it require…
ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs
Aleksandar Zlateski, Kisuk Lee, H. Sebastian Seung
Sliding window convolutional networks (ConvNets) have become a popular approach to computer vision problems such as image segmentation, and object detection and localization. Here…