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Henry Hoffman

Researcher at Massachusetts Institute of Technology

Publications -  7
Citations -  1316

Henry Hoffman is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Instructions per cycle & Program counter. The author has an hindex of 6, co-authored 7 publications receiving 1291 citations.

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Journal ArticleDOI

The Raw microprocessor: a computational fabric for software circuits and general-purpose programs

TL;DR: The Raw microprocessor research prototype uses a scalable instruction set architecture to attack the emerging wire-delay problem by providing a parallel, software interface to the gate, wire and pin resources of the chip.
Proceedings ArticleDOI

A 16-issue multiple-program-counter microprocessor with point-to-point scalar operand network

TL;DR: The 0.15/spl mu/m 6M microprocessor as mentioned in this paper uses 16 unique instructions per cycle and uses an on-chip point-to-point scalar operand network to transfer operands among distributed functional units.

A 16-issue multiple-program-counter microprocessor with point-to-point scalar operand network

TL;DR: This microprocessor explores an architectural solution to scalability problems in scalar operand networks by using an on-chip point-to-point scalaroperand network to transfer operands among distributed functional units.
Proceedings ArticleDOI

ATAC: Improving performance and programmability with on-chip optical networks

TL;DR: ATAC, a new manycore architecture that capitalizes on the recent advances in optics to address a number of challenges that future manycore designs will face, is introduced and Consumer Tagging is introduced, a novel programming model that leverages ATAC's strengths to provide high performance and scalability.

Seec: a framework for self-aware management of goals and constraints in computing systems (power-aware computing, accuracy-aware computing, adaptive computing, autonomic computing)

TL;DR: This thesis describes the SEEC framework and evaluates it in several case studies, demonstrating that SEEC can have a positive impact on real systems by understanding high level goals and adapting to meet those goals online.