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Joshua Fazekas

dblp:03/5365 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2006
—ORCID · none

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

Systems, architecture and hardware · 4

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
2 papers
Electronic design automation · 41% Reconfigurable computing and FPGAs · 31% Integrated circuit design · 15%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Electronic design automation › high-level synthesis
hardware generation
0.112006
An automated, reconfigurable, low-power RFID tag · DAC 2006
Integrated circuit design
low-power circuit design
0.112006
An automated, reconfigurable, low-power RFID tag · DAC 2006
Electronic design automation › high-level synthesis › hardware compilation
c-to-hardware compilation
0.112005
An FPGA-based VLIW processor with custom hardware execution · FPGA 2005
Reconfigurable computing and FPGAs
FPGA-based processor implementation
0.112005
An FPGA-based VLIW processor with custom hardware execution · FPGA 2005
Electronic design automation
high-level synthesis
0.112005
An FPGA-based VLIW processor with custom hardware execution · FPGA 2005
Processor architecture and microarchitecture › instruction-level parallelism › VLIW
VLIW processor
0.112005
An FPGA-based VLIW processor with custom hardware execution · FPGA 2005

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

ANSI-C specification · 0.1custom instruction synthesis · 0.1VLIW processing · 0.1
YearPublicationVenuePosition
2006 An automated, reconfigurable, low-power RFID tag
abstract
This paper describes an ultra low power active RFID tag and its automated design flow. RFID primitives to be supported by the tag are enumerated with RFID macros and the behavior of each primitive is specified using ANSI-C within the template to automatically generate the tag controller. Two power saving components, a passive transceiver/burst switch and a smart buffer, are presented to save power and increase tag lifetime. Based on a test program, the processors required 183, 43, and 19 μ&J per transaction for StrongARM, XScale, and EISC processors, respectively. Three hardware controllers using a Fusion FPGA, Coolrunner II CPLD, and ASIC required 13 nJ, 1.3 nJ, and 0.07 nJ per transaction.
Alex K. Jones, Raymond R. Hoare, Swapna R. Dontharaju, Shen Chih Tung, Ralph Sprang, Joshua Fazekas, James T. Cain, Marlin H. Mickle
DAC6
2006 A Field Programmable RFID Tag and Associated Design Flow
abstract
Current radio frequency identification (RFID) systems generally have long design times and low tolerance to changes in specification. This paper describes a field programmable, low-power active RFID tag, and its associated specification and automated design flow. RFID primitives to be supported by the tag are enumerated with RFID macros, or assembly-like descriptions of the tag operations. From these, the RFID preprocessor generates templates automatically. The behavior of each RFID primitive is specified using ANSI C in the template. The resulting file is compiled by the RFID compiler. A smart buffer sits between the transceiver and the tag controller, to detect whether incoming packets are intended for the tag. By doing so, the main controller may remain powered down to reduce power consumption. Two system-on-a-chip implementation strategies are presented. First, a microprocessor based system for which a C program is automatically generated. The second includes a block of low-power FPGA logic. The user supplied RFID logic in ANSI-C is automatically converted into combinational VHDL by the RFID compiler. Based on a test program, the processors required 183, 43, and 19 muJ per transaction for StrongARM, XScale, and EISC processors, respectively. By replacing the processor with a Coolrunner II, the controller can be reduced to 1.11 nJ per transaction
Alex K. Jones, Raymond R. Hoare, Swapna R. Dontharaju, Shen Chih Tung, Ralph Sprang, Joshua Fazekas, James T. Cain, Marlin H. Mickle
FCCM6
2006 Reducing power while increasing performance with supercisc
abstract
Multiprocessor Systems on Chips (MPSoCs) have become a popular architectural technique to increase performance. However, MPSoCs may lead to undesirable power consumption characteristics for computing systems that have strict power budgets, such as PDAs, mobile phones, and notebook computers. This paper presents the super-complex instruction-set computing (SuperCISC) Embedded Processor Architecture and, in particular, investigates performance and power consumption of this device compared to traditional processor architecture-based execution. SuperCISC is a heterogeneous, multicore processor architecture designed to exceed performance of traditional embedded processors while maintaining a reduced power budget compared to low-power embedded processors. At the heart of the SuperCISC processor is a multicore VLIW (Very Large Instruction Word) containing several homogeneous execution cores/functional units. In addition, complex and heterogeneous combinational hardware function cores are tightly integrated to the core VLIW engine providing an opportunity for improved performance and reduced energy consumption. Our SuperCISC processor core has been synthesized for both a 90-nm Stratix II Field Programmable Gate Aray (FPGA) and a 160-nm standard cell Application-Specific Integrated Circuit (ASIC) fabrication process from OKI, each operating at approximately 167 MHz for the VLIW core. We examine several reasons for speedup and power improvement through the SuperCISC architecture, includingpredicated control flow,cycle compression, and a reduction in arithmetic power consumption, which we callpower compression. Finally, testing our SuperCISC processor with multimedia and signal-processing benchmarks, we show how the SuperCISC processor can provide performance improvements ranging from 7X to 160X with an average of 60X, whilealsoproviding orders of magnitude of power improvements for the computational kernels. The power improvements for our benchmark kernels range from just over 40X to over 400X, with an average savings exceeding 130X. By combining these power and performance improvements, our total energy improvements all exceed 1000X. As these savings are limited to the computational kernels of the applications, which often consume approximately 90% of the execution time, we expect our savings to approach the ideal application improvement of 10X.
Alex K. Jones, Raymond R. Hoare, Dara Kusic, Gayatri Mehta, Joshua Fazekas, John Foster 0001
ACM Trans. Embed. Comput. Syst.5
2005 An FPGA-based VLIW processor with custom hardware execution
abstract
The capability and heterogeneity of new FPGA (Field Programmable Gate Array) devices continues to increase with each new line of devices. Efficiently programming these devices is increasing in difficulty. However, FPGAs continue to be utilized for algorithms traditionally targeted to embedded DSP microprocessors such as signal and image processing applications.This paper presents an architecture that combines VLIW (Very Large Instruction Word) processing with the capability to introduce application specific customized instructions and complex hardware functions. To support this architecture, a compilation and design automation flow are described for programs written in C.Several design tradeoffs for the architecture were examined including number of VLIW functional units and register file size. The architecture was implemented on an Altera Stratix II FPGA. The Stratix II device was selected because it offers a large number of high-speed DSP (digital signal processing) blocks that execute multiply accumulate operations.We show that our combined VLIW with hardware functions exhibit as much as 230X speedup and 63X on average for computational kernels for a set of benchmarks. This allows for an overall speedup of 30X and 12X on average for signal processing benchmarks from the MediaBench.
Alex K. Jones, Raymond R. Hoare, Dara Kusic, Joshua Fazekas, John Foster 0001
FPGA4