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aichip_paper_list

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

bt

bt - flexible backtesting for Python

convnet-burden

Memory consumption and FLOP count estimates for convnets

convnet.pytorch

ConvNet training using pytorch

convolution_kernel

Accelerating CNN's convolution operation on GPUs by using memory-efficient data access patterns.

cupy

NumPy-like API accelerated with CUDA

cutlass-gpgpu-sim

dl-on-silicon

research, experimentation and implementation of hardware-agnostic accelerated DL framework

easyquant

EasyQuant(EQ) is an efficient and simple post-training quantization method via effectively optimizing the scales of weights and activations.

efficient_frontier

Markowitz portfolio optimisation (efficient frontier) in Python

gilbut_portfolio

길벗출판사 포트폴리오

gpgpu-ramulator-simulator

Replace original DRAM model in GPGPU-sim with Ramulator DRAM model

gpgpu-sim-approximate

gpgpu-sim_distribution-1

GPGPU-Sim provides a detailed simulation model of a contemporary GPU running CUDA and/or OpenCL workloads and now includes an integrated (and validated) energy model, GPUWattch.

phase-aware-warp-scheduling-policy-on-gpgpu-sim-nvidia-tesla-c2050-architecture-

public

pytorch-playground

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

pytorch-quant

DL quantization for pytorch

rowhammer-experience

sit-python

Python versions of SIT programs