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Tuesday, March 28 • 10:20 - 12:20
Student Research Competition

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Thierno Barry / CEA

Automated Combination of Tolerance and Control Flow Integrity Countermeasures against Multiple Fault Attacks

Fault injection attacks are considered as one of the most fearsome threats against secure embedded systems. Existing software countermeasures are either applied at the source code level where cautions must be taking to prevent the compiler from altering the countermeasure during compilation, or at the assembly code level where the code lacks semantic information, which as a result, limits the possibilities of code transformation and leads to significant overheads. Moreover, to protect against various fault models, countermeasures are usually applied incrementally without taking into account the impact one can have on another.

This paper presents an automated application of several countermeasures against fault attacks, that combines fault tolerance and control flow integrity. The fault tolerance schemes are parameterizable over the width of the fault injection, and the number of fault injections that the secured code must be protected against. The countermeasures are applied by a modified compiler based on clang/LLVM. As a result, the produced code is both optimized and secure by design. Performance and security evaluations on different benchmarks show reduced performance overheads compared to existing solutions, with the expected security level.
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Michael Haidl / University of Muenster

Bringing Next Generation C++ to GPUs: The LLVM-based PACXX Approach

In this paper, we describe PACXX -- our approach for programming Graphics Processing Unit (GPU) in C++. PACXX is based on Clang and LLVM and allows to compile arbitrary C++ code for GPU execution. PACXX enables developers to use all the convenient features of modern C++14: type deduction, lambda expressions, and algorithms from the Standard Template Library (STL). Using PACXX, a GPU program is written as a single C++ program, rather than two distinct host and kernel programs as in CUDA or OpenCL. Using LLVM's just-in-time compilation capabilities, PACXX generates efficient GPU code at runtime.

We demonstrate how PACXX supports a composable GPU programming approach: developers compose their applications from simple and reusable patterns. We extend the range-v3 library which is currently developed as the next generation of the C++ Standard Template Library (STL) to allow for GPU programming using ranges.

We describe how PACXX enables developers to use multi-staging in C++ to optimize their GPU programs at runtime. PACXX provides an easy-to-use and type-safe API avoiding the pitfalls of string manipulation for multi-staging known from other GPU programming models (e.g., OpenCL).

Our evaluation shows that using PACXX achieves competitive performance to CUDA, and our extended range-v3 programming approach can outperform Nvidia's highly-tuned Thrust library.
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This submission is a compilation of:
Multi-Stage Programming for GPUs in Modern C++ using PACXX published in the proceedings of the 9th GPGPU Workshop @ PPoPP 2016 - http://dl.acm.org/citation.cfm?id=2884049 Towards Composable GPU Programming: Programming GPUs with Eager Actions and Lazy Views published in the proceedings of the 8th PMAM Workshop @ PPoPP 2017 (to appear) https://github.com/michel-steuwer/publications/raw/master/2017/PMAM-2017.pdf
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Georgios Zacharopoulos / Università della Svizzera Italiana

Data Reuse Analysis for Automated Synthesis of Custom Instructions in Sliding Window Applications

The efficiency of accelerators supporting complex instructions is often limited by their input/output bandwidth requirements. To overcome this bottleneck, we herein introduce a novel methodology that, following a static code analysis approach, harnesses data reuse in-between multiple iteration of loop bodies to reduce the amount of data transfers. Our methodology, building upon the features offered by the LLVM-Polly framework, enables the automated design of fully synthesisable and highly-efficient accelerators. Our approach is targeted towards sliding window kernels, which are employed in many applications in the signal and image processing domain.

NOTE: This paper has been published in IMPACT 2017 Seventh International Workshop on Polyhedral Compilation Techniques Jan 23, 2017, Stockholm, Sweden
In conjunction with HiPEAC 2017. http://impact.gforge.inria.fr/impact2017
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Lawrence Esswood / University Of Cambridge

ELF GOT Problems? CFI Can Help.

Control-Flow Integrity (CFI) techniques make the deployment of malicious exploits harder by constraining the control flow of programs to that of a statically analyzed control-flow graph (CFG). This is made harder when position-independent dynamically shared objects are compiled separately, and then linked together only at runtime by a dynamic linker. Deploying CFI only on statically linked objects ensures that control flow enters only the correct procedure linkage table (PLT) entry, not where that trampoline jumps to; it leaves a weak link at the boundaries of shared objects that attackers can use to gain control. We show that manipulation of the PLT GOT has a long history of exploitation, and is still being used today against real binaries - even with state of the art CFI enforcement. PLT-CFI is a CFI implementation for the ELF dynamic-linkage model, designed to work along-side existing CFI implementations that ensure correct control flow within a single dynamic shared object (DSO). We make modifications to the LLVM stack to insert dynamic checks into the PLT that ensure correct control flow even in the presence of an unknown base address of a dynamic library, while maintaining the ability to link in a lazy fashion and allowing new implementations (e.g., plug-ins) to be loaded at runtime. We make only minor ABI changes, and still offer full backwards compatibility with binaries compiled without our scheme. Furthermore, we deployed our CFI scheme for both AMD64 and AArch64 on the FreeBSD operating system and measured performance.
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Andres Noetzli / Stanford University

LifeJacket: Verifying Precise Floating-Point Optimizations in LLVM

Users depend on correct compiler optimizations but floating-point arithmetic is difficult to optimize transparently. Manually reasoning about all of floating-point arithmetic’s esoteric properties is error-prone and increases the cost of adding new optimizations. We present an approach to automate reasoning about precise floating-point optimizations using satisfiability modulo theories (SMT) solvers. We implement the approach in LifeJacket, a system for automatically verifying precise floating-point optimizations for the LLVM assembly language. We have used LifeJacket to verify 43 LLVM optimizations and to discover eight incorrect ones, including three previously unreported problems. LifeJacket is an open source extension of the Alive system for optimization verification.
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Sam Ainsworth / University of Cambridge

Software Prefetching for Indirect Memory Accesses

Many modern data processing and HPC workloads are heavily memory-latency bound. A tempting proposition to solve this is software prefetching, where special non-blocking loads are used to bring data into the cache hierarchy just before being required. However, these are difficult to insert to effectively improve performance, and techniques for automatic insertion are currently limited.

This paper develops a novel compiler pass to automatically generate software prefetches for indirect memory accesses, a special class of irregular accesses often seen in high-performance workloads. We evaluate this across a wide set of systems, all of which gain benefit from the technique. Across a set of memory-bound benchmarks, our automated pass achieves average speedups of 1.3x and 1.1x for an Intel Haswell processor and an ARM Cortex-A57, both out-of-order

Speakers
avatar for Sam Ainsworth

Sam Ainsworth

University of Cambridge
avatar for Thierno Barry

Thierno Barry

PhD Candidate, CEA
avatar for Michael Haidl

Michael Haidl

Research Associate, University of Muenster
AN

Andres Noetzli

Stanford University
avatar for Georgios Zacharopoulos

Georgios Zacharopoulos

PhD Student, Università della Svizzera italiana (USI Lugano)


Tuesday March 28, 2017 10:20 - 12:20
E2 2 (Günter Hotz Hall)

Attendees (37)