Parameterized Hardware Design with Latency-Abstract Interfaces
January 04, 2024 Β· Declared Dead Β· + Add venue
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Rachit Nigam, Ethan Gabizon, Edmund Lam, Carolyn Zech, Jonathan Balkind, Adrian Sampson
arXiv ID
2401.02570
Category
cs.PL: Programming Languages
Cross-listed
cs.AR
Citations
0
Last Checked
4 months ago
Abstract
Hardware designs must use latency-insensitive (LI) interfaces when timing is input-dependent. When timing is input-independent, designs should use latency-sensitive (LS) interfaces for maximum performance. However, designs commonly use LI interfaces to integrate with externally generated LS modules--from, e.g., IP generators, high-level synthesis, or domain specific languages. In every fully integrated design, such uses of LI represent pure overhead. The challenge is that generators can dramatically change timing interfaces of the modules to meet performance objectives, and LI interfaces act as a useful design abstraction and enable timing adaptation. We define latency-abstract (LA) interfaces, a new design abstraction, which provide the timing adaptability of LI interfaces at design-time and the efficient integration of LS interfaces. LA interfaces use output parameters, a novel compile-time mechanism for child modules to return values parent modules, to abstract and encapsulate timing behaviors at design time. During design elaboration, LA interfaces are compiled into efficient LS interfaces based on parameter values. While an attractive option, LA interfaces inherit the complexities of parameterized hardware design: the user must reason how parameters influence timing behaviors of modules and ensure that designs adapt to interface changes. To address this challenge and demonstrate the utility of LA interfaces, we design Lilac, a parameterized HDL that uses a type system track the influence of parameters on timing behaviors and formally guarantee that every parameterization of an LA design results in a circuit without structural hazards.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Programming Languages
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions
R.I.P.
π»
Ghosted
Glow: Graph Lowering Compiler Techniques for Neural Networks
R.I.P.
π»
Ghosted
Learnable Programming: Blocks and Beyond
R.I.P.
π»
Ghosted
Scenic: A Language for Scenario Specification and Scene Generation
R.I.P.
π»
Ghosted
Vandal: A Scalable Security Analysis Framework for Smart Contracts
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted