Demo Data from EDBT 2026 / reviewers in the wild / expert
Ganapati Srinivasa
dblp:04/11098
· DBLP profile ↗
5ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0002-1008-2893ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 5
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
3 papers |
Processor architecture and microarchitecture · 66% GPUs and heterogeneous computing · 12% Electronic design automation · 12% |
Topics — the 8 heaviest of 9, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Processor architecture and microarchitecture › multicore design
heterogeneous multicore |
0.2 | 1 | 2015 | Wavelet-Based Trace Alignment Algorithms for Heterogeneous Architectures · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2015 |
Processor architecture and microarchitecture › multicore design › heterogeneous multicore
single-ISA heterogeneous cores |
0.2 | 1 | 2015 | Wavelet-Based Trace Alignment Algorithms for Heterogeneous Architectures · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2015 |
Processor architecture and microarchitecture › multicore design › heterogeneous multicore
asymmetric multicore |
0.1 | 1 | 2012 | QuickIA: Exploring heterogeneous architectures on real prototypes · HPCA 2012 |
Electronic design automation
design space exploration |
0.1 | 1 | 2012 | QuickIA: Exploring heterogeneous architectures on real prototypes · HPCA 2012 |
GPUs and heterogeneous computing
heterogeneous architecture |
0.1 | 1 | 2012 | QuickIA: Exploring heterogeneous architectures on real prototypes · HPCA 2012 |
Processor architecture and microarchitecture › multicore design
heterogeneous cores |
0.1 | 1 | 2012 | The Forgotten 'Uncore': On the Energy-Efficiency of Heterogeneous Cores · USENIX ATC 2012 |
Performance modeling and evaluation
workload characterization |
0.1 | 1 | 2015 | Wavelet-Based Trace Alignment Algorithms for Heterogeneous Architectures · IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2015 |
Processor architecture and microarchitecture
multicore design |
0.0 | 1 | 2012 | The Forgotten 'Uncore': On the Energy-Efficiency of Heterogeneous Cores · USENIX ATC 2012 |
Methods — techniques the papers use, named apart from their topics
wavelet-based similarity metric · 0.2dynamic programming · 0.2prototyping · 0.1case study · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Wavelet-Based Trace Alignment Algorithms for Heterogeneous ArchitecturesabstractHeterogeneous architectures with single-instruction set architecture (ISA) asymmetric cores can improve both the performance and energy efficiency of software execution by dynamically selecting the most appropriate core type to run each execution thread. In this paper, we propose a trace-based methodology to explore power and performance benefits of single-ISA heterogeneous core architectures. The basic idea is to collect multiple traces by running a workload on different homogeneous platforms, and to align these traces for offline analysis. For this, we propose a wavelet-based similarity metric, which captures both fine-grain and coarse-grain software phases across different traces. Then, we propose a scalable dynamic programming algorithm to optimize this metric to align the traces. Our experiments show that the runtime and energy values predicted by our offline methodology have good accuracy with respect to the real measurements from a prototype heterogeneous system. Muhammet Mustafa Ozdal, Aamer Jaleel, Paolo Narváez, Steven M. Burns, Ganapati Srinivasa |
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. | 5 |
| 2013 | Trace alignment algorithms for offline workload analysis of heterogeneous architecturesabstractHeterogeneous architectures with single-ISA asymmetric cores have the potential to improve both the performance and energy efficiency of software execution by dynamically selecting the most appropriate core type to run each execution thread. In this paper, we propose a trace-based methodology to explore power and performance benefits of single-ISA heterogeneous core architectures. The basic idea is to collect multiple traces by running a workload on different homogeneous platforms, and to align these traces for offline analysis. For this, we propose a wavelet-based similarity metric, which captures both fine-grain and coarse-grain software phases across different traces. Then, we propose a scalable dynamic programming algorithm to optimize this metric to align the traces. Our experiments show that the runtime and energy values predicted by our offline methodology have good accuracy with respect to the real measurements from a prototype heterogeneous system. The proposed methodology can enable design space exploration of single-ISA heterogeneous multi-core systems using traces from off-the-shelf homogeneous systems. Muhammet Mustafa Ozdal, Aamer Jaleel, Paolo Narváez, Steven M. Burns, Ganapati Srinivasa |
ICCAD | 5 |
| 2012 | QuickIA: Exploring heterogeneous architectures on real prototypesabstractOver the last decade, homogeneous multi-core processors emerged and became the de-facto approach for offering high parallelism, high performance and scalability for a wide range of platforms. We are now at an interesting juncture where several critical factors (smaller form factor devices, power challenges, need for specialization, etc) are guiding architects to consider heterogeneous chips and platforms for the next decade and beyond. Exploring heterogeneous architectures is challenging since it involves re-evaluating architecture options, OS implications and application development. In this paper, we describe these research challenges and then introduce a heterogeneous prototype platform called QuickIA that enables rapid exploration of heterogeneous architectures employing multiple generations of Intel processors for evaluating the implications of asymmetry and FPGAs to experiment with specialized processors or accelerators. We also show example case studies using the QuickIA research prototype to highlight its value in conducting heterogeneous architecture, OS and applications research. Bhushan Chitlur, Ganapati Srinivasa, Scott Hahn, Dheeraj Reddy, David A. Koufaty, Paul Brett, Abirami Prabhakaran, Li Zhao 0002, Nelson Ijih, Suchit Subhaschandra, Sabina Grover, Xiaowei Jiang, Ravi R. Iyer 0001 |
HPCA | 2 |
| 2012 | Scaling the "Memory Wall": Designer trackabstractDRAM has been the technology for computer main memory since Intel released the first commercial DRAM chip (i1103) in 1970. As technology scales and demand for memory performance, it seems DRAM is facing several challenges. Many other memory technologies are anticipated to replace it but none has emerged as a clear winner thus far. In this paper we post the question. Is it possible to re-examine the design of DRAM to continue its life for another decade at least? Shih-Lien Lu, Tanay Karnik, Ganapati Srinivasa, Kai-Yuan Chao, Doug Carmean, Jim Held |
ICCAD | 3 |
| 2012 | The Forgotten 'Uncore': On the Energy-Efficiency of Heterogeneous Cores
Vishal Gupta 0001, Paul Brett, David A. Koufaty, Dheeraj Reddy, Scott Hahn, Karsten Schwan, Ganapati Srinivasa |
USENIX ATC | 7 |