Sensitivity-Based Sparse Matrix除了将异常值隔离到稀疏矩阵中之外,本文还发现将一小部分高度敏感性的权重值隔离到稀疏矩阵中将会显著提升量化的性能。 Dense-and-Sparse Kernel Implementation 本文为了有效处理非均匀量化值,实现了基于查找表的CUDAKernel来进行矩阵-向量乘,这些kernel将压缩的权重加载,然后反量化到FP16,...
TLDR: Deploying LLMs is difficult due to their large memory size. This can be addressed with reduced precision quantization. But a naive method hurts performance. We address this with a new Dense-and-Sparse Quantization method. Dense-and-Sparse splits weight matrices into two components: A den...
QuantizationPruningMatrix multiplication accelerationConvolutionLSTMIn this paper, we present hardware accelerators created with high-level synthesis techniques for sparse and dense matrix multiplication operations. The cores can operate with different precisions and are designed to be integrated in a ...
In our previous work [18], we investigated the accuracy effects of arbitrary quantization with LSTM and CNN layers, and we presented hardware for independent sparse and dense computations using small Xilinx Zynq SoC devices. The sparse architecture was an extension of matrix–vector hardware, which...
out = tf.quantization.fake_quant_with_min_max_args(out, min=-100, max=100, name="out") # if we have bias if bias_in_size: out = nn_ops.bias_add(out, in_bias) compare_tflite_with_tvm( data_array, inq_data.name, [inq_data], [out], quantized=True, input_range=input_range...
英文摘要:We present Dense-SfM, a novel Structure from Motion (SfM) framework designed for dense and accurate 3D reconstruction from multi-view images. Sparse keypoint matching, which traditional SfM methods often rely on, limits both accuracy and point density, especially in texture-less areas. ...
The U-Net architecture employs the encoder–decoder structure and skip-connections to construct the segmentation map from a dense feature representation. The vanilla U-Net architecture finds difficulty to perform at par, where the ROI is sparse [2]. Therefore, custom encoder–decoder architectures, ...
Product Quantization:我们还可以使用乘积量化来进一步压缩向量大小,其基本原理是将d维的向量分解成s个子向量,每个子向量采用k-means量化,并使用t比特存储。比如,一个768维的向量占用了768\times 32比特,通过将其分解为192个8比特的子向量,该向量的大小便压缩到了192\times 8比特,即原始大小的1/16,平均来说,每个...
In techniques for fast dense patch search and quantization, partition center patches are determined for partitions of example image patches. Patch groups of an image each include si
In techniques for fast dense patch search and quantization, partition center patches are determined for partitions of example image patches. Patch groups of an image each include si