| 1. |
- Arelakis, Angelos, 1984, et al.
(författare)
-
A Cache System and a Method of Operating a Cache
- 2016
-
Patent (övrigt vetenskapligt/konstnärligt)abstract
- n one embodiment, a computer cache is extended with structures that can (1) establish the frequency by which distinct values occur in the cache and use that information to (2) compress values in caches into dense codes using a plurality of statistical-based compression techniques and (3) decompress densely coded values to realize caches that can store information densely that can be retrieved with low overhead.
|
|
| 2. |
- Arelakis, Angelos, 1984, et al.
(författare)
-
HyComp: A Hybrid Cache Compression Method for Selection of Data-Type-Specific Compression Methods
- 2015
-
Ingår i: 48th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2015, Waikiki, United States, 5-9 December 2015. - New York, NY, USA : ACM. - 1072-4451. - 9781450340342 ; 05-09-December-2015, s. 38-49
-
Konferensbidrag (refereegranskat)abstract
- Proposed cache compression schemes make design-time assumptions on value locality to reduce decompression latency. For example, some schemes assume that common values are spatially close whereas other schemes assume that null blocks are common. Most schemes, however, assume that value locality is best exploited by fixed-size data types (e.g., 32-bit integers). This assumption falls short when other data types, such as floating-point numbers, are common. This paper makes two contributions. First, HyComp - a hybrid cache compression scheme - selects the best-performing compression scheme, based on heuristics that predict data types. Data types considered are pointers, integers, floating-point numbers and the special (and trivial) case of null blocks. Second, this paper contributes with a compression method that exploits value locality in data types with predefined semantic value fields, e.g., as in the exponent and the mantissa in floating-point numbers. We show that HyComp, augmented with the proposed floating-point-number compression method, offers superior performance in comparison with prior art.
|
|
| 3. |
- Arelakis, Angelos, 1984
(författare)
-
Statistical Compression Cache Designs
- 2015
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- On-chip caches are essential as they bridge the growing speed-gap between off-chip memory and processors. To this end, processing cores are sacrificed for more cache space in the chip's real estate, possibly affecting the cache access time and power dissipation. An alternative to increase the effective cache capacity without enlarging its size is cache compression. However, the compression and decompression processes required add complexity and latency; especially decompression lies in the critical memory access path. Prior work focuses on methods that target lower decompression latency by sacrificing important gains in compressibility. On the other hand, this thesis focuses on cache designs that exploit more advanced compression methods, i.e., statistical compression.The thesis first contributes with an abstract value-aware cache model, which shows that applications often exhibit value locality, and establishes that ideally, by storing each appeared value exactly once, important compression opportunities open up. Motivated by this, the thesis proposes SC^2, a Huffman-based statistical compression cache design. The thesis tackles the problem of statistics acquisition by building a sampling mechanism in hardware. It finds that value locality is rather stable over long time-periods, hence code generation can be offloaded in software. Then it builds the support for compression and decompression in hardware, deals with practical issues such as cache space management, and finally makes a detailed exploration of statistical compression in the last-level cache. Unfortunately, this approach cannot be straightforwardly applied to data types that contain semantically well-defined data fields. Among such types, the thesis focuses on the common double-precision floating-point data and explores a different avenue to extract value locality by considering the different fields (sign, exponent and mantissa) in isolation. Contrary to prior observations, it is shown that the mantissa exhibits significant value locality if it is further partitioned. Then a novel statistical compression method, called FP-H, tailored for cache compression is proposed. Finally, the thesis makes the observation that none of the compressed cache designs, including state of the art, are hitherto always better than others. Hence the thesis establishes HyComp, a practical cache design that adopts hybrid compression for the first time where one out of data-type specific compression methods is selected through heuristics. HyComp offers robust compressibility across applications that manipulate diverse data types, without affecting decompression but only slightly impacting compression latency.
|
|
