Rimas Avizienis

dblp:60/5149 · also Rimas R. Avizienis · DBLP profile ↗
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7ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

Systems, architecture and hardware · 7Software engineering, systems software and programming languages · 1

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 architecture, parallel and distributed computing, and storage systems
4 papers
Processor architecture and microarchitecture · 34% Electronic design automation · 20% Hardware accelerators and domain-specific architectures · 17%

Topics — the 11 heaviest of 12, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware accelerators and domain-specific architectures
data-parallel accelerator
0.322013
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Processor architecture and microarchitecture › vector processor
vector-thread architecture
0.322013
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Processor architecture and microarchitecture
SIMD
0.222013
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
GPUs and heterogeneous computing › GPU microarchitecture
SIMT architecture
0.212013
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
Electronic design automation
high-level synthesis
0.112012
Chisel: constructing hardware in a Scala embedded language · DAC 2012
Parallel and multicore computing › data parallelism
SIMD vectorization
0.112011
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Performance modeling and evaluation › simulation
architectural simulation
0.112010
RAMP gold: an FPGA-based architecture simulator for multiprocessors · DAC 2010
Processor architecture and microarchitecture
multicore design
0.112010
RAMP gold: an FPGA-based architecture simulator for multiprocessors · DAC 2010
Reconfigurable computing and FPGAs
FPGA design flow
0.012012
Chisel: constructing hardware in a Scala embedded language · DAC 2012
Electronic design automation
design space exploration
0.012011
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Parallel and multicore computing › parallel architecture
MIMD architecture
0.012011
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011

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

VLSI implementation · 0.3design space exploration · 0.2type inference · 0.1functional programming · 0.1microbenchmarking · 0.1host multithreading · 0.1cycle-accurate timing model · 0.1FPGA prototyping · 0.1
YearPublicationVenuePosition
2015 Raven: A 28nm RISC-V vector processor with integrated switched-capacitor DC-DC converters and adaptive clocking
Yunsup Lee, Brian Zimmer, Andrew Waterman, Alberto Puggelli, Jaehwa Kwak, Ruzica Jevtic, Ben Keller, Stevo Bailey, Milovan Blagojevic, Pi-Feng Chiu, Henry Cook, Rimas Avizienis, Brian C. Richards, Elad Alon, Borivoje Nikolic, Krste Asanovic
Hot Chips Symposium12
2013 The RISC-V instruction set
Andrew Waterman, Yunsup Lee, Rimas Avizienis, Henry Cook, David A. Patterson 0001, Krste Asanovic
Hot Chips Symposium3
2013 Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators
abstract
We present a taxonomy and modular implementation approach for data-parallel accelerators, including the MIMD, vector-SIMD, subword-SIMD, SIMT, and vector-thread (VT) architectural design patterns. We introduce Maven, a new VT microarchitecture based on the traditional vector-SIMD microarchitecture, that is considerably simpler to implement and easier to program than previous VT designs. Using an extensive design-space exploration of full VLSI implementations of many accelerator design points, we evaluate the varying tradeoffs between programmability and implementation efficiency among the MIMD, vector-SIMD, and VT patterns on a workload of compiled microbenchmarks and application kernels. We find the vector cores provide greater efficiency than the MIMD cores, even on fairly irregular kernels. Our results suggest that the Maven VT microarchitecture is superior to the traditional vector-SIMD architecture, providing both greater efficiency and easier programmability.
Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic
ACM Trans. Comput. Syst.2
2012 Chisel: constructing hardware in a Scala embedded language
abstract
In this paper we introduce Chisel, a new hardware construction language that supports advanced hardware design using highly parameterized generators and layered domain-specific hardware languages. By embedding Chisel in the Scala programming language, we raise the level of hardware design abstraction by providing concepts including object orientation, functional programming, parameterized types, and type inference. Chisel can generate a high-speed C++-based cycle-accurate software simulator, or low-level Verilog designed to map to either FPGAs or to a standard ASIC flow for synthesis. This paper presents Chisel, its embedding in Scala, hardware examples, and results for C++ simulation, Verilog emulation and ASIC synthesis.
Jonathan Bachrach, Huy Vo, Brian C. Richards, Yunsup Lee, Andrew Waterman, Rimas Avizienis, John Wawrzynek, Krste Asanovic
DAC6
2011 The Maven vector-thread architecture
Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic
Hot Chips Symposium2
2011 Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators
abstract
We present a taxonomy and modular implementation approach for data-parallel accelerators, including the MIMD, vector-SIMD, subword-SIMD, SIMT, and vector-thread (VT) architectural design patterns. We have developed a new VT microarchitecture, Maven, based on the traditional vector-SIMD microarchitecture that is considerably simpler to implement and easier to program than previous VT designs. Using an extensive design-space exploration of full VLSI implementations of many accelerator design points, we evaluate the varying tradeoffs between programmability and implementation efficiency among the MIMD, vector-SIMD, and VT patterns on a workload of microbenchmarks and compiled application kernels. We find the vector cores provide greater efficiency than the MIMD cores, even on fairly irregular kernels. Our results suggest that the Maven VT microarchitecture is superior to the traditional vector-SIMD architecture, providing both greater efficiency and easier programmability.
Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic
ISCA2
2010 RAMP gold: an FPGA-based architecture simulator for multiprocessors
abstract
We present RAMP Gold, an economical FPGA-based architecture simulator that allows rapid early design-space exploration of manycore systems. The RAMP Gold prototype is a high-throughput, cycle-accurate full-system simulator that runs on a single Xilinx Virtex-5 FPGA board, and which simulates a 64-core shared-memory target machine capable of booting real operating systems. To improve FPGA implementation efficiency, functionality and timing are modeled separately and host multithreading is used in both models. We evaluate the prototype's performance using a modern parallel benchmark suite running on our manycore research operating system, achieving two orders of magnitude speedup compared to a widely-used software-based architecture simulator.
Zhangxi Tan, Andrew Waterman, Rimas Avizienis, Yunsup Lee, Henry Cook, David A. Patterson 0001, Krste Asanovic
DAC3