Experimental study of aggressive undervolting in FPGAs

In this work, we evaluate aggressive undervolting, i.e., voltage scaling below the nominal level to reduce the energy consumption of Field Programmable Gate Arrays (FPGAs). Usually, voltage guardbands are added by chip vendors to ensure the worst-case process and environmental scenarios. Through experimenting on several FPGA architectures, we measure this voltage guardband to be on average 39% of the nominal level, which in turn, delivers more than an order of magnitude power savings. However, further undervolting below the voltage guardband may cause reliability issues as the result of the circuit delay increase, i.e., start to appear faults. We extensively characterize the behavior of these faults in terms of the rate, location, type, as well as sensitivity to environmental temperature, with a concentration of on-chip memories, or Block RAMs (BRAMs). Finally, we evaluate a typical FPGA-based Neural Network (NN) accelerator under low-voltage BRAM operations. In consequence, the substantial NN energy savings come with the cost of NN accuracy loss. To attain power savings without NN accuracy loss, we propose a novel technique that relies on the deterministic behavior of undervolting faults and can limit the accuracy loss to 0.1% without any timing-slack overhea

A Demo of FPGA Aggressive Voltage Downscaling: Power and Reliability Tradeoffs

The power consumption of digital circuits, e.g., Field Programmable Gate Arrays (FPGAs), is directly related to their operating supply voltages. On the other hand, usually, chip vendors introduce a conservative voltage guardband below the standard nominal level to ensure the correct functionality of the design in worst-case process and environmental scenarios. For instance, this voltage guardband is empirically measured to be 12%, 20%, and 16% of the nominal level in commercial CPUs [1], Graphics Processing Units (GPUs) [2], and Dynamic RAMs (DRAMs) [3], respectively. However, in many real-world applications, this guardband is extremely conservative and eliminating it can result in significant power savings without any overhead. Motivated by these studies, we aim to extend the undevolting technique to commercial FPGAs. Toward this goal, we will practically demonstrate the voltage guardband for a representative Xilinx FPGA, with a preliminary concentration on on-chip memories, or Block RAMs (BRAMs).We thank Pradip Bose, Alper Buyuktosunoglu, and Augusto Vega from IBM Watson for their contribution to this work. The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the LEGaTO Project (www.legato-project.eu), grant agreement nº 780681.Peer ReviewedPostprint (author's final draft

A runtime heuristic to selectively replicate tasks for application-specific reliability targets

In this paper we propose a runtime-based selective task replication technique for task-parallel high performance computing applications. Our selective task replication technique is automatic and does not require modification/recompilation of OS, compiler or application code. Our heuristic, we call App_FIT, selects tasks to replicate such that the specified reliability target for an application is achieved. In our experimental evaluation, we show that App FIT selective replication heuristic is low-overhead and highly scalable. In addition, results indicate that complete task replication is overkill for achieving reliability targets. We show that with App FIT, we can tolerate pessimistic exascale error rates with only 53% of the tasks being replicated.This work was supported by FI-DGR 2013 scholarship and the European Community’s Seventh Framework Programme [FP7/2007-2013] under the Mont-blanc 2 Project (www.montblanc-project.eu), grant agreement no. 610402 and in part by the European Union (FEDER funds) under contract TIN2015-65316-P.Peer ReviewedPostprint (author's final draft

Empowering a helper cluster through data-width aware instruction selection policies

Narrow values that can be represented by less number of bits than the full machine width occur very frequently in programs. On the other hand, clustering mechanisms enable cost- and performance-effective scaling of processor back-end features. Those attributes can be combined synergistically to design special clusters operating on narrow values (a.k.a. helper cluster), potentially providing performance benefits. We complement a 32-bit monolithic processor with a low-complexity 8-bit helper cluster. Then, in our main focus, we propose various ideas to select suitable instructions to execute in the data-width based clusters. We add data-width information as another instruction steering decision metric and introduce new data-width based selection algorithms which also consider dependency, inter-cluster communication and load imbalance. Utilizing those techniques, the performance of a wide range of workloads are substantially increased; helper cluster achieves an average speedup of 11% for a wide range of 412 apps. When focusing on integer applications, the speedup can be as high as 22% on averagePeer ReviewedPostprint (published version

FPGA checkpointing for scientific computing

The use of FPGAs in computational workloads is becoming increasingly popular due to the flexibility of these devices in comparison to ASICs, and their low power consumption compared to GPUs and CPUs. However, scientific applications run for long periods of time and the hardware is always subject to failures due to either soft or hard errors. Thus, it is important to protect these long running jobs with fault tolerance mechanisms. Checkpoint-Restart is a popular technique in high-performance computing that allows large scale applications to cope with frequent failures. In this work we approach the fault tolerance of CPU-FPGA heterogeneous applications from a high level by using OmpSs@FPGA environment and a multi-level checkpointing library. We analyse the performance of several different applications and we understand what kind of overheads we can expect from checkpointing computational workloads running on FPGAs. Our results demonstrate overheads as low as 0.16% and 0.66% when checkpointing very frequently, indicating that this technique is efficient and does not add a significant amount of overhead to the system. In addition, we showcase a proof of concept for checkpointing partial data of the FPGA task itself. This can prove useful for workloads in which most data is offloaded to the FPGA memory at once and do not constantly move all the data between the accelerator and the CPU.This research has received funding from the European Union’s Horizon 2020 research and innovation programme under projects EuroEXA (grant agreement nº 754337) and eProcessor (grant agreement nº 956702).Peer ReviewedPostprint (author's final draft

Implications of non-volatile memory as primary storage for database management systems

Traditional Database Management System (DBMS) software relies on hard disks for storing relational data. Hard disks are cheap, persistent, and offer huge storage capacities. However, data retrieval latency for hard disks is extremely high. To hide this latency, DRAM is used as an intermediate storage. DRAM is significantly faster than disk, but deployed in smaller capacities due to cost and power constraints, and without the necessary persistency feature that disks have. Non-Volatile Memory (NVM) is an emerging storage class technology which promises the best of both worlds. It can offer large storage capacities, due to better scaling and cost metrics than DRAM, and is non-volatile (persistent) like hard disks. At the same time, its data retrieval time is much lower than that of hard disks and it is also byte-addressable like DRAM. In this paper, we explore the implications of employing NVM as primary storage for DBMS. In other words, we investigate the modifications necessary to be applied on a traditional relational DBMS to take advantage of NVM features. As a case study, we have modified the storage engine (SE) of PostgreSQL enabling efficient use of NVM hardware. We detail the necessary changes and challenges such modifications entail and evaluate them using a comprehensive emulation platform. Results indicate that our modified SE reduces query execution time by up to 40% and 14.4% when compared to disk and NVM storage, with average reductions of 20.5% and 4.5%, respectively.The research leading to these results has received funding from the European Union’s 7th Framework Programme under grant agreement number 318633, the Ministry of Science and Technology of Spain under contract TIN2015-65316-P, and a HiPEAC collaboration grant awarded to Naveed Ul Mustafa.Peer ReviewedPostprint (author's final draft

Circuit design of a novel adaptable and reliable L1 data cache

This paper proposes a novel adaptable and reliable L1 data cache design (Adapcache) with the unique capability of automatically adapting itself for different supply voltage levels and providing the highest reliability. Depending on the supply voltage level, Adapcache defines three operating modes: In high supply voltages, Adapcache provides reliability through single-bit parity. In middle range of supply voltages, Adapcache writes data to two separate cache-lines simultaneously in order to use one line for error recovery when the other line is faulty. In near threshold supply voltages, Adapcache writes data to three separate cache-lines simultaneously in order to provide the correct data based on bitwise majority voter. We design and simulate one embodiment of the Adapcache as a 64-KB L1 data cache with 45-nm CMOS technology at 2GHz processor frequency for almost nominal supply voltages (1V-0.6V), at 900MHz for middle supply voltages (0.6V-0.4V), and at 400MHz for near threshold supply voltages (0.4V-0.32V). According to our experimental results, the energy reduction and latency as well as cache capacity usage are improved compared to typical previous proposals, Triple Modular Redundancy (TMR) and Double Modular Redundancy (DMR) techniques and also to the state of the art proposal, Parichute Error Correction Code (ECC).Postprint (published version

Vector processing-aware advanced clock-gating techniques for low-power fused multiply-add

The need for power efficiency is driving a rethink of design decisions in processor architectures. While vector processors succeeded in the high-performance market in the past, they need a retailoring for the mobile market that they are entering now. Floating-point (FP) fused multiply-add (FMA), being a functional unit with high power consumption, deserves special attention. Although clock gating is a well-known method to reduce switching power in synchronous designs, there are unexplored opportunities for its application to vector processors, especially when considering active operating mode. In this research, we comprehensively identify, propose, and evaluate the most suitable clock-gating techniques for vector FMA units (VFUs). These techniques ensure power savings without jeopardizing the timing. We evaluate the proposed techniques using both synthetic and “real-world” application-based benchmarking. Using vector masking and vector multilane-aware clock gating, we report power reductions of up to 52%, assuming active VFU operating at the peak performance. Among other findings, we observe that vector instruction-based clock-gating techniques achieve power savings for all vector FP instructions. Finally, when evaluating all techniques together, using “real-world” benchmarking, the power reductions are up to 80%. Additionally, in accordance with processor design trends, we perform this research in a fully parameterizable and automated fashion.The research leading to these results has received funding from the RoMoL ERC Advanced Grant GA 321253 and is supported in part by the European Union (FEDER funds) under contract TTIN2015-65316-P. The work of I. Ratkovic was supported by a FPU research grant from the Spanish MECD.Peer ReviewedPostprint (author's final draft

FIMSIM: A fault injection infrastructure for microarchitectural simulators

Fault injection is a widely used approach for experiment-based dependability evaluation in which faults can be injected to the hardware, to the simulator or to the software. Simulation based fault injection is more appealing for researchers, since it can be utilized at the early design stage of the processor. As such, it enables a preliminary analysis of the correlation between the criticality of circuit level faults and their impact on applications. However, the lack of publicly available fault injectors for microarchitecture level simulators brings extra burden of designing and implementing fault injectors to the researchers who evaluate microarchitecture dependability. In this study, we present FIMSIM, to the best of our knowledge, the first publicly available fault injection simulator at the microarchitecture level. FIMSIM is a compact tool which is capable of injecting transient, permanent, intermittent and multi-bit faults. Therefore, FIMSIM provides the opportunity to comprehensively evaluate the vulnerability of different microarchitectural structures against different fault models.Postprint (published version