Personne

Mikhail Asiatici

Cette personne n’est plus à l’EPFL

Publications associées (13)

Request, Coalesce, Serve, and Forget: Miss-Optimized Memory Systems for Bandwidth-Bound Cache-Unfriendly Applications on FPGAs

Applications such as large-scale sparse linear algebra and graph analytics are challenging to accelerate on FPGAs due to the short irregular memory accesses, resulting in low cache hit rates. Nonblocking caches reduce the bandwidth required by misses by re ...

ASSOC COMPUTING MACHINERY2022

How Many CPU Cores is an FPGA Worth? Lessons Learned from Accelerating String Sorting on a CPU-FPGA System

Paolo Ienne, Mikhail Asiatici, Damian Maiorano

String sorting is a fundamental kernel of string matching and database index construction; yet, it has not been studied as extensively as fixed-length keys sorting. Because processing variable-length keys in hardware is challenging, it is no surprise that ...

SPRINGER2021

Miss-Optimized Memory Systems: Turning Thousands of Outstanding Misses into Reuse Opportunities

Mikhail Asiatici

Even if Dennard scaling came to an end fifteen years ago, Moore's law kept fueling an exponential growth in compute performance through increased parallelization. However, the performance of memory and, in particular, Dynamic Random Access Memory (DRAM), ...

EPFL2021

Large-Scale Graph Processing on FPGAs with Caches for Thousands of Simultaneous Misses

Paolo Ienne, Mikhail Asiatici

Efficient large-scale graph processing is crucial to many disciplines. Yet, while graph algorithms naturally expose massive parallelism opportunities, their performance is limited by the memory system because of irregular memory accesses. State-of-the-art ...

IEEE COMPUTER SOC2021

FPGAs in the Datacenters: the Case of Parallel Hybrid Super Scalar String Sample Sort

Paolo Ienne, Mikhail Asiatici, Damian Maiorano

String sorting is an important part of database and MapReduce applications; however, it has not been studied as extensively as sorting of fixed-length keys. Handling variable-length keys in hardware is challenging and it is no surprise that no string sorte ...

IEEE COMPUTER SOC2020

In Search of Lost Bandwidth: Extensive Reordering of DRAM Accesses on FPGA

Paolo Ienne, Mikhail Asiatici, Gabor Andras Csordas

For efficient acceleration on FPGA, it is essential for external memory to match the throughput of the processing pipelines. However, the usable DRAM bandwidth decreases significantly if the access pattern causes frequent row conflicts. Memory controllers ...

IEEE COMPUTER SOC2019

FPGAs rely on massive datapath parallelism to accelerate applications even with a low clock frequency. However, applications such as sparse linear algebra and graph analytics have their throughput limited by irregular accesses to external memory for which ...

ASSOC COMPUTING MACHINERY2019

DynaBurst: Dynamically Assemblying DRAM Bursts over a Multitude of Random Accesses

Paolo Ienne, Mikhail Asiatici

The effective bandwidth of the FPGA external memory, usually DRAM, is extremely sensitive to the access pattern. Nonblocking caches that handle thousands of outstanding misses (miss-optimized memory systems) can dynamically improve bandwidth utilization wh ...

IEEE2019

Through-Glass Vias for Glass Interposers and MEMS Packaging Applications Fabricated Using Magnetic Assembly of Microscale Metal Wires

Mikhail Asiatici, Göran Stemme

A through-glass via (TGV) provides a vertical electrical connection through a glass substrate. TGVs are used in advanced packaging solutions, such as glass interposers and wafer-level packaging of microelectromechanical systems (MEMS). However, TGVs are ch ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Virtualized Execution Runtime for FPGA Accelerators in the Cloud

Paolo Ienne, Mikhail Asiatici, Nithin George

FPGAs offer high performance coupled with energy efficiency making them extremely attractive computational resources within a cloud ecosystem. However, to achieve this integration and make them easy to program, we first need to enable users with varying ex ...

2017

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