Title: Helium: lifting high-performance stencil kernels from stripped x86 binaries to halide DSL code

Abstract

Highly optimized programs are prone to bit rot, where performance quickly becomes suboptimal in the face of new hardware and compiler techniques. In this paper we show how to automatically lift performance-critical stencil kernels from a stripped x86 binary and generate the corresponding code in the high-level domain-specific language Halide. Using Halide's state-of-the-art optimizations targeting current hardware, we show that new optimized versions of these kernels can replace the originals to rejuvenate the application for newer hardware. The original optimized code for kernels in stripped binaries is nearly impossible to analyze statically. Instead, we rely on dynamic traces to regenerate the kernels. We perform buffer structure reconstruction to identify input, intermediate and output buffer shapes. Here, we abstract from a forest of concrete dependency trees which contain absolute memory addresses to symbolic trees suitable for high-level code generation. This is done by canonicalizing trees, clustering them based on structure, inferring higher-dimensional buffer accesses and finally by solving a set of linear equations based on buffer accesses to lift them up to simple, high-level expressions. Helium can handle highly optimized, complex stencil kernels with input-dependent conditionals. We lift seven kernels from Adobe Photoshop giving a 75 % performance improvement, four kernelsmore » from Irfan View, leading to 4.97 x performance, and one stencil from the mini GMG multigrid benchmark netting a 4.25 x improvement in performance. We manually rejuvenated Photoshop by replacing eleven of Photoshop's filters with our lifted implementations, giving 1.12 x speedup without affecting the user experience.« less

Authors:

Mendis, Charith ^[1]; Bosboom, Jeffrey ^[1]; Wu, Kevin ^[1]; Kamil, Shoaib ^[1]; Ragan-Kelley, Jonathan ^[2]; Paris, Sylvain ^[3]; Zhao, Qin ^[4]; Amarasinghe, Saman ^[1]

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+ Show Author Affiliations

1. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Computer Science and Artificial Intelligence Lab. (CSAIL)
2. Stanford Univ., Palo Alto, CA (United States)
3. Adobe, Cambridge, MA (United States)
4. Google, Cambridge, MA (United States)

Publication Date:

Wed Jun 03 00:00:00 EDT 2015

Research Org.:

Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Computer Science and Artificial Intelligence Lab. (CSAIL)

Sponsoring Org.:

USDOE Office of Science (SC); Defense Advanced Research Projects Agency (DARPA)

OSTI Identifier:

1457399

Grant/Contract Number:  

SC0005288; SC0008923

Resource Type:

Accepted Manuscript

Journal Name:

ACM SIGPLAN Notices

Additional Journal Information:

Journal Volume: 2015; Journal ID: ISSN 0362-1340

Publisher:

ACM

Country of Publication:

United States

Language:

English

Subject:

97 MATHEMATICS AND COMPUTING