Compile time | EPFL Graph Search

In computer science, compile time (or compile-time) describes the time window during which a language's statements are converted into 0s and 1s for the computer to understand. The term is used as an adjective to describe concepts related to the context of program compilation, as opposed to concepts related to the context of program execution (runtime). For example, compile-time requirements are programming language requirements that must be met by source code before compilation and compile-time properties are properties of the program that can be reasoned about during compilation. The actual length of time it takes to compile a program is usually referred to as compilation time. Compile time/Early binding vs Run time The determination of execution model have been set during the compile time stage. Run time- the method of execution and allocation - have been set during the run time and are based on the run time dynamicity. Overview Most compilers have at least the

Software Support for Non-Volatile Memory (NVM) Programming

David Teksen Aksun

Non-Volatile Memory (NVM) is an emerging type of memory device that provides fast, byte-addressable, and high-capacity durable storage. NVM sits on the memory bus and allows durable data structures designs similar to the in-memory equivalent ones. Expensive serialization/deserialization operations, usually associated with block-based storage, are not necessary. Unfortunately, using NVM is not as simple as placing a data structure in NVM and expecting persistence. As NVM sits on the memory bus, processor caches buffer the cache lines from it that are referenced by load and store instructions. The volatility of the caches and possible power failures at a random point in a program complicate the design and require ways to handle these failures. Prior work focused on implementing crash-consistency mechanisms to correctly recover a program's data after a failure. The goal was to minimize the use of costly cache line write-back and fence instructions, which are necessary for correct durability. Moreover, commercial NVM devices are slower compared to DRAM and affect the design. In addition to performance overheads, correctly implementing crash consistency is hard. The programmers need to carefully reason about cache line write-back instructions and the order of persistent writes. Finding bugs can take from minutes to hours. In this thesis, we use checkpointing as an effective crash-consistency mechanism with low overhead for building durable data structures. We also describe an inter-procedural dataflow analysis for fast detection of NVM programming bugs. We show the practicality of these ideas through three primary contributions and their implementations. Firstly, we present InCLL to address NVM checkpointing. InCLL is a novel technique that uses fine-grained checkpointing and in-cache-line logging to minimize the number of explicit write-back and fence instructions in the fast path of data structure modifications. We evaluate InCLL both on DRAM and Optane devices for the Masstree data structure. Secondly, we present a new checkpointing design, CpNvm, which minimizes NVM write-back instructions on the critical path of the execution. We achieve low overheads for Masstree and Memcached for write-heavy workloads, and almost no overheads for read-only workloads. In addition, we present FlowNvm to find NVM programming bugs. FlowNvm can identify NVM programming pattern violations and anti-patterns at compile-time using inter-procedural dataflow analysis.

EPFL2021

Accelerating parser combinators with macros

Eric Beguet, Manohar Jonnalagedda

Parser combinators provide an elegant way of writing parsers: parser implementations closely follow the structure of the underlying grammar, while accommodating interleaved host language code for data processing. However, the host language features used for composition introduce substantial overhead, which leads to poor performance. In this paper, we present a technique to systematically eliminate this overhead. We use Scala macros to analyse the grammar specification at compile-time and remove composition, leaving behind an efficient top-down, recursive-descent parser. We compare our macro-based approach to a staging-based approach using the LMS framework, and provide an experience report in which we discuss the advantages and drawbacks of both methods. Our library outperforms Scala's standard parser combinators on a set of benchmarks by an order of magnitude, and is 2x faster than code generated by LMS.

ACM Press2014

Scala AST Persistence

Eugene Burmako, Mathieu Baptiste Demarne, Adrien Ghosn

The Scala compiler uses ASTs (abstract syntax trees) as an intermediate representation before generating bytecode. With the development of Scala macros which expand trees at compile time, being able to access, modify and recompose ASTs within the compilation scope is becoming more and more important. One of the common scenarios of using macros is inspecting abstract syntax trees within reach in order to learn more about the code being transformed, to apply more powerful optimizations, etc. However, arguments to macros can depend on third-party libraries, which are precompiled as bytecode and don't have their ASTs available. It would therefore be great to have a way to publish ASTs along with the bytecode. The publishing of those ASTs should be a choice of the programmer and should take as little space as possible in order to be transparent to the user.

2014

Software Support for Non-Volatile Memory (NVM) Programming

David Teksen Aksun

EPFL2021