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CC 2020
Sat 22 - Wed 26 February 2020 San Diego, California, United States
Sat 22 Feb 2020 13:00 - 13:22 - Session 2 Techniques for Specific Domains Chair(s): Dongyoon Lee

Usage of high-level intermediate representations promises the generation of fast code from a high-level description, improving the productivity of developers while achieving the performance traditionally only reached with low-level programming approaches.

High-level IRs come in two flavors: 1) domain-specific IRs designed to express only for a specific application area; or 2) generic high-level IRs that can be used to generate high-performance code across many domains. Developing generic IRs is more challenging but offers the advantage of reusing a common compiler infrastructure various applications.

In this paper, we extend a generic high-level IR to enable efficient computation with sparse data structures. Crucially, we encode sparse representation using reusable dense building blocks already present in the high-level IR. We use a form of dependent types to model sparse matrices in CSR format by expressing the relationship between multiple dense arrays explicitly separately storing the length of rows, the column indices, and the non-zero values of the matrix.

We demonstrate that we achieve high-performance compared to spare low-level library code using our extended generic high-level code generator. On an Nvidia GPU, we outperform the highly tuned Nvidia cuSparse implementation of \gls{spmv} multiplication across 28 sparse matrices of varying sparsity on average by 1.7\times1.7×.

Sat 22 Feb
Times are displayed in time zone: Pacific Time (US & Canada) change

13:00 - 14:30
Session 2 Techniques for Specific DomainsMain Conference
Chair(s): Dongyoon LeeStony Brook University
13:00
22m
Research paper
Generating Fast Sparse Matrix Vector Multiplication From a High Level Generic Functional IR
Main Conference
Federico PizzutiUniversity of Edinburgh, Michel SteuwerUniversity of Glasgow, Christophe DubachUniversity of Edinburgh
13:22
22m
Research paper
A Study of Event Frequency Profiling with Differential Privacy
Main Conference
Hailong ZhangOhio State University, Yu Hao, Sufian LatifOhio State University, USA, Raef BassilyOhio State University, USA, Atanas RountevOhio State University
13:45
22m
Research paper
Improving Database Query Performance with Automatic Fusion
Main Conference
Hanfeng ChenMcGill University, Canada, Alexander KrolikMcGill University, Canada, Bettina KemmeMcGill University, Canada, Clark VerbruggeMcGill University, Canada, Laurie HendrenMcGill University, Canada
14:07
22m
Research paper
Robust Quantization of Deep Neural Networks
Main Conference
Youngseok KimHanyang University, Korea, Junyeol LeeHanyang University, Korea, Younghoon KimHanyang University, Korea, Jiwon SeoHanyang University