Concept

LLVM

Publications associées (33)

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Felix Schürmann, Pramod Shivaji Kumbhar, Omar Awile, Ioannis Magkanaris

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

ACM2023

A Dynamically Scheduled HLS Flow in MLIR

Morten Borup Petersen

In High-Level Synthesis (HLS), we consider abstractions that span from software to hardware and target heterogeneous architectures. Therefore, managing the complexity introduced by this is key to implementing good, maintainable, and extendible HLS compiler ...

2022

From C/C plus plus Code to High-Performance Dataflow Circuits

Paolo Ienne, Andrea Guerrieri, Lana Josipovic

High-level synthesis (HLS) tools typically generate statically scheduled datapaths. Static scheduling implies that the resulting circuits have a hard time exploiting parallelism in code with potential memory dependences, with control dependences, or where ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Virtual ADTs for Portable Metaprogramming

Martin Odersky, Nicolas Alexander Stucki

Scala 3 provides a metaprogramming interface that represents the abstract syntax tree definitions using algebraic data types. To allow the compiler to freely evolve without breaking the metaprogramming interface, we present virtual algebraic data types (or ...

ASSOC COMPUTING MACHINERY2021

Verification of Software Network Functions with No Verification Expertise

Arseniy Zaostrovnykh

Software network functions (NFs), such as a network address translator, load balancer, or proxy, promise to bring flexibility and rapid innovation to computer networks and to reduce operational costs. However, continuous updates and flexibility typically c ...

EPFL2020

Enabling Accuracy-Aware Quantum Compilers using Symbolic Resource Estimation

Mathias Soeken, Giulia Meuli

Approximation errors must be taken into account when compiling quantum programs into a low-level gate set. We present a methodology that tracks such errors automatically and then optimizes accuracy parameters to guarantee a specified overall accuracy while ...

ASSOC COMPUTING MACHINERY2020

Just-in-time performance without warm-up

Denys Shabalin

Scala has been developed as a language that deeply integrates with the Java ecosystem. It offers seamless interoperability with existing Java libraries. Since the Scala compiler targets Java bytecode, Scala programs have access to high-performance runtimes ...

EPFL2020

Optimized Memory Access For Dynamically Scheduled High Level Synthesis

Paolo Ienne, Atri Bhattacharyya

Dynamically-scheduled elastic circuits generated by High-Level Synthesis (HLS) tools are inherently out-of-order, following the flow of data rather than the evolution of an instruction pointer. Components of the circuit which access memory need to be conne ...

2018

A Programming Model and Foundation for Lineage-Based Distributed Computation

Philipp Haller

The most successful systems for "big data'' processing have all adopted functional APIs. We present a new programming model we call function passing designed to provide a more principled substrate, or middleware, upon which to build data-centric distribute ...

Cambridge University Press2018

Interflow: interprocedural flow-sensitive type inference and method duplication

Martin Odersky, Denys Shabalin

Scala heavily relies on a number of object-oriented abstractions to support its feature-rich collections library. There are known techniques that optimize those abstractions away in just-in-time (JIT) compilers, but applying them in the ahead-of-time (AOT) ...

2018

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search