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Mark Leone

dblp:l/MarkLeone · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
2 papers
Rendering · 100%
Software engineering, system software, and programming languages
1 paper
Runtime systems and virtual machines · 100%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering › ray tracing
path tracing
0.312018
Manuka: A Batch-Shading Architecture for Spectral Path Tracing in Movie Production · ACM Trans. Graph. 2018
Rendering
global illumination
0.112018
Manuka: A Batch-Shading Architecture for Spectral Path Tracing in Movie Production · ACM Trans. Graph. 2018
Rendering
light transport
0.112018
Manuka: A Batch-Shading Architecture for Spectral Path Tracing in Movie Production · ACM Trans. Graph. 2018
Rendering › sampling
multiple importance sampling
0.112018
Manuka: A Batch-Shading Architecture for Spectral Path Tracing in Movie Production · ACM Trans. Graph. 2018
Rendering › GPU rendering › shader-based rendering
deferred shading
0.112005
Lpics: a hybrid hardware-accelerated relighting engine for computer cinematography · ACM Trans. Graph. 2005
Runtime systems and virtual machines › dynamic compilation
just-in-time compilation
0.011996
Optimizing ML with Run-Time Code Generation · PLDI 1996
Runtime systems and virtual machines › dynamic compilation
run-time code generation
0.011996
Optimizing ML with Run-Time Code Generation · PLDI 1996

Methods — techniques the papers use, named apart from their topics

shade-before-hit paradigm · 0.3pattern generation shaders · 0.3locality of reference · 0.3procedural renderman shaders · 0.1numerical surface response estimation · 0.1partial evaluation · 0.0multi-stage programming · 0.0
YearPublicationVenuePosition
2018 Manuka: A Batch-Shading Architecture for Spectral Path Tracing in Movie Production
abstract
The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture: to enable the creation of visually rich computer generated imagery for visual effects in movie production. Following in the footsteps of reyes over the past 30 years, this means supporting extremely complex geometry, texturing, and shading. In the current generation of renderers, it is essential to support very accurate global illumination as a means to naturally tie together different assets in a picture. This is commonly achieved with Monte Carlo path tracing, using a paradigm often called shade on hit , in which the renderer alternates tracing rays with running shaders on the various ray hits. The shaders take the role of generating the inputs of the local material structure, which is then used by path-sampling logic to evaluate contributions and to inform what further rays to cast through the scene. We propose a shade before hit paradigm instead and minimise I/O strain on the system, leveraging locality of reference by running pattern generation shaders before we execute light transport simulation by path sampling. We describe a full architecture built around this approach, featuring spectral light transport and a flexible implementation of multiple importance sampling ( mis ), resulting in a system able to support a comparable amount of extensibility to what made the reyes rendering architecture successful over many decades.
Luca Fascione, Johannes Hanika, Mark Leone, Marc Droske, Jorge Schwarzhaupt, Tomás Davidovic, Andrea Weidlich, Johannes Meng
ACM Trans. Graph.3
2005 Lpics: a hybrid hardware-accelerated relighting engine for computer cinematography
abstract
In computer cinematography, the process of lighting design involves placing and configuring lights to define the visual appearance of environments and to enhance story elements. This process is labor intensive and time consuming, primarily because lighting artists receive poor feedback from existing tools: interactive previews have very poor quality, while final-quality images often take hours to render.This paper presents an interactive cinematic lighting system used in the production of computer-animated feature films containing environments of very high complexity, in which surface and light appearances are described using procedural RenderMan shaders. Our system provides lighting artists with high-quality previews at interactive framerates with only small approximations compared to the final rendered images. This is accomplished by combining numerical estimation of surface response, image-space caching, deferred shading, and the computational power of modern graphics hardware.Our system has been successfully used in the production of two feature-length animated films, dramatically accelerating lighting tasks. In our experience interactivity fundamentally changes an artist's workflow, improving both productivity and artistic expressiveness.
Fabio Pellacini, Kiril Vidimce, Aaron E. Lefohn, Alex Mohr, Mark Leone, John Warren
ACM Trans. Graph.5
1996 Optimizing ML with Run-Time Code Generation
abstract
We describe the design and implementation of a compiler that automatically translates ordinary programs written in a subset of ML into code that generates native code at run time. Run-time code generation can make use of values and invariants that cannot be exploited at compile time, yielding code that is often superior to statically optimal code. But the cost of optimizing and generating code at run time can be prohibitive. We demonstrate how compile-time specialization can reduce the cost of run-time code generation by an order of magnitude without greatly affecting code quality. Several benchmark programs are examined, which exhibit an average cost of only six cycles per instruction generated at run time.
Peter Lee 0001, Mark Leone
PLDI2
1994 Lightweight Run-Time Code Generation
Mark Leone, Peter Lee 0001
PEPM1